diff --git a/doc/api.rst b/doc/api.rst
index 77a44d5294..335bc186aa 100755
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -8,41 +8,10 @@ spikeinterface.core
     .. autofunction:: load
     .. autoclass:: BaseRecording
         :members:
-    .. automethod:: BaseRecording.save
-    .. automethod:: BaseRecording.save_to_memory
-    .. automethod:: BaseRecording.save_to_folder
-    .. automethod:: BaseRecording.save_to_zarr
-    .. automethod:: BaseRecording.dump
-    .. automethod:: BaseRecording.dump_to_json
-    .. automethod:: BaseRecording.dump_to_pickle
-    .. automethod:: BaseRecording.remove_channels
-    .. automethod:: BaseRecording.set_probe
-    .. automethod:: BaseRecording.set_probegroup
-    .. automethod:: BaseRecording.remove_probe
-    .. automethod:: BaseRecording.select_channels_with_probe
-    .. automethod:: BaseRecording.select_channels_with_probegroup
-    .. automethod:: BaseRecording.split_by
     .. autoclass:: BaseSorting
         :members:
-    .. automethod:: BaseSorting.save
-    .. automethod:: BaseSorting.save_to_memory
-    .. automethod:: BaseSorting.save_to_folder
-    .. automethod:: BaseSorting.save_to_zarr
-    .. automethod:: BaseSorting.dump
-    .. automethod:: BaseSorting.dump_to_json
-    .. automethod:: BaseSorting.dump_to_pickle
-    .. automethod:: BaseSorting.split_by
-    .. automethod:: BaseSorting.register_recording
     .. autoclass:: BaseSnippets
         :members:
-    .. automethod:: BaseSnippets.save
-    .. automethod:: BaseSnippets.save_to_memory
-    .. automethod:: BaseSnippets.save_to_folder
-    .. automethod:: BaseSnippets.save_to_zarr
-    .. automethod:: BaseSnippets.dump
-    .. automethod:: BaseSnippets.dump_to_json
-    .. automethod:: BaseSnippets.dump_to_pickle
-    .. automethod:: BaseSnippets.remove_channels
     .. autoclass:: BaseEvent
         :members:
     .. autoclass:: SortingAnalyzer
@@ -56,7 +25,6 @@ spikeinterface.core
     .. autoclass:: Motion
         :members:
     .. autoclass:: BinaryRecordingExtractor
-    .. autoclass:: ZarrRecordingExtractor
     .. autoclass:: BinaryFolderRecording
     .. autoclass:: NumpyFolderSorting
     .. autoclass:: NpyFolderSnippets
@@ -201,8 +169,8 @@ spikeinterface.preprocessing
 .. automodule:: spikeinterface.preprocessing
 
     .. autofunction:: apply_preprocessing_pipeline
-    .. autofunction:: get_preprocessing_dict_from_analyzer
-    .. autofunction:: get_preprocessing_dict_from_file
+    .. autofunction:: get_preprocessing_list_from_analyzer
+    .. autofunction:: get_preprocessing_list_from_file
     .. autofunction:: astype
     .. autofunction:: average_across_direction
     .. autofunction:: bandpass_filter
@@ -254,7 +222,6 @@ spikeinterface.postprocessing
 .. automodule:: spikeinterface.postprocessing
 
     .. autofunction:: compute_noise_levels
-    .. autofunction:: compute_template_metrics
     .. autofunction:: compute_principal_components
     .. autofunction:: compute_spike_amplitudes
     .. autofunction:: compute_unit_locations
@@ -439,7 +406,6 @@ Deprecated
     :noindex:
 
     .. autofunction:: apply_sortingview_curation
-    .. autofunction:: get_potential_auto_merge
     .. autoclass:: CurationSorting
     .. autoclass:: MergeUnitsSorting
     .. autoclass:: SplitUnitSorting
diff --git a/doc/development/development.rst b/doc/development/development.rst
index b8c8761aa8..82b17e7a35 100644
--- a/doc/development/development.rst
+++ b/doc/development/development.rst
@@ -384,6 +384,7 @@ In order to check if your spike sorter is installed, a :code:`try` - :code:`exce
 sorter is implemented in Python (installed with the package :code:`myspikesorter`), this block will look as follows:
 
 .. code-block:: python
+
     import importlib.util
     if importlib.util.find_spec("myspikesorter"):
         HAVE_MYSORTER = True
diff --git a/doc/how_to/index.rst b/doc/how_to/index.rst
index 3c631f0376..92cd0312d2 100644
--- a/doc/how_to/index.rst
+++ b/doc/how_to/index.rst
@@ -7,6 +7,7 @@ Guides on how to solve specific, short problems in SpikeInterface. Learn how to.
     :maxdepth: 1
 
     viewers
+    read_various_formats
     customize_a_plot
     combine_recordings
     process_by_channel_group
diff --git a/doc/how_to/physical_units.rst b/doc/how_to/physical_units.rst
index a76c791ec5..be8213c98e 100644
--- a/doc/how_to/physical_units.rst
+++ b/doc/how_to/physical_units.rst
@@ -41,7 +41,7 @@ Converting to Physical Units
 ----------------------------
 
 SpikeInterface provides two preprocessing classes for converting recordings to physical units. Both wrap the
-``RecordingExtractor`` class and ensures that the data is returned in physical units when calling `get_traces <https://spikeinterface.readthedocs.io/en/stable/api.html#spikeinterface.core.BaseRecording.get_traces>`_
+``BaseRecording`` class and ensures that the data is returned in physical units when calling `get_traces <https://spikeinterface.readthedocs.io/en/stable/api.html#spikeinterface.core.BaseRecording.get_traces>`_
 
 1. ``scale_to_uV``: The primary function for extracellular recordings. SpikeInterface is centered around
     extracellular recordings, and this function is designed to convert the data to microvolts (µV).
diff --git a/doc/how_to/read_various_formats.rst b/doc/how_to/read_various_formats.rst
index 1e8ee0d5bc..59dc090d07 100644
--- a/doc/how_to/read_various_formats.rst
+++ b/doc/how_to/read_various_formats.rst
@@ -108,7 +108,7 @@ stream information can be retrieved by using the
 
 
 The
-:py:func::literal:`~spikeinterface.extractors.read_spike2`\` function is equivalent to instantiating a :py:class:`\ ~spikeinterface.extractors.Spike2RecordingExtractor\`
+:py:func:`~spikeinterface.extractors.read_spike2` function is equivalent to instantiating a :py:class:`~spikeinterface.extractors.Spike2RecordingExtractor`
 object:
 
 .. code:: ipython3
diff --git a/doc/how_to/unsigned_to_signed.rst b/doc/how_to/unsigned_to_signed.rst
index 87a861bcc9..1e3f59b756 100644
--- a/doc/how_to/unsigned_to_signed.rst
+++ b/doc/how_to/unsigned_to_signed.rst
@@ -16,8 +16,8 @@ For those that want a deeper understanding of dtypes `NumPy provides a great exp
 For our purposes it is important to know that many pieces of recording equipment opt to store their electrophysiological data as unsigned integers
 (e.g., Intan, Maxwell Biosystems, 3Brain Biocam).
 Similarly to signed integers, in order to convert to real units these file formats only need to store a :code:`gain`
-and an :code:`offset`. Our :code:`RecordingExtractor`'s maintain the dtype that the file format utilizes, which means that some of our
-:code:`RecordingExtractor`'s will have unsigned dtypes.
+and an :code:`offset`. Our :code:`BaseRecording`'s maintain the dtype that the file format utilizes, which means that some of our
+:code:`BaseRecording`'s will have unsigned dtypes.
 
 The problem with using unsigned dtypes is that many types of functions (including the ones we use from :code:`SciPy`) perform poorly with unsigned integers.
 This is made worse by the fact that these failures are silent (i.e. no error is triggered but the operation leads to nonsensical data). So the
diff --git a/doc/modules/core.rst b/doc/modules/core.rst
index b10ae14a99..fcc92b5a6e 100644
--- a/doc/modules/core.rst
+++ b/doc/modules/core.rst
@@ -438,7 +438,7 @@ All computed extensions will be automatically propagated or merged when curating
 
 
 Handling very large datasets: ``lazy`` mode
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 For very large datasets with tens-to-hundreds millions of spikes, the :code:`SortingAnalyzer` computations can be very
 memory intensive. By default, in fact, the :code:`SortingAnalyzer` computes and stores all the data in memory.
@@ -1007,7 +1007,7 @@ LEGACY objects
 --------------
 
 WaveformExtractor
-^^^^^^^^^^^^^^^^^
+~~~~~~~~~~~~~~~~~
 
 This is now a legacy object that can still be accessed through the :py:class:`MockWaveformExtractor`. It is kept
 for backward compatibility. You can convert a ``WaveformExtractor`` to a ``SortingAnalyzer``
diff --git a/doc/modules/curation.rst b/doc/modules/curation.rst
index d9b877c9da..0ce4edcc94 100644
--- a/doc/modules/curation.rst
+++ b/doc/modules/curation.rst
@@ -139,6 +139,7 @@ which applies a set of thresholds based on the available metrics (template/quali
         fail_label="bad",
         column_name="simple_threshold"
     )
+
 The returned ``labels`` is a ``pandas.DataFrame`` with the unit_ids as index and the assigned labels in the ``simple_threshold`` column.
 
 
diff --git a/doc/modules/metrics.rst b/doc/modules/metrics.rst
index 1095553852..a9b9e920a9 100644
--- a/doc/modules/metrics.rst
+++ b/doc/modules/metrics.rst
@@ -85,7 +85,7 @@ metric information. For example, you can get the list of available metrics and t
     'velocity_above': 'Velocity of the spike propagation above the max channel in um/ms',
     'velocity_below': 'Velocity of the spike propagation below the max channel in um/ms',
     'waveform_baseline_flatness': 'Ratio of max baseline amplitude to max waveform amplitude. Lower = flatter baseline.'
-}
+    }
 
 
 
diff --git a/doc/tutorials_custom_index.rst b/doc/tutorials_custom_index.rst
index 65b9c84543..d50fa56e22 100755
--- a/doc/tutorials_custom_index.rst
+++ b/doc/tutorials_custom_index.rst
@@ -196,27 +196,27 @@ The :code:`widgets` module contains several plotting routines (widgets) for visu
 .. grid:: 1 2 2 3
    :gutter: 2
 
-   .. grid-item-card:: RecordingExtractor Widgets
+   .. grid-item-card:: BaseRecording Widgets
       :link-type: ref
       :link: sphx_glr_tutorials_widgets_plot_1_rec_gallery.py
       :img-top: /tutorials/widgets/images/thumb/sphx_glr_plot_1_rec_gallery_thumb.png
-      :img-alt: Recording Widgets
+      :img-alt: BaseRecording Widgets
       :class-card: gallery-card
       :text-align: center
 
-   .. grid-item-card:: SortingExtractor Widgets
+   .. grid-item-card:: BaseSorting Widgets
       :link-type: ref
       :link: sphx_glr_tutorials_widgets_plot_2_sort_gallery.py
       :img-top: /tutorials/widgets/images/thumb/sphx_glr_plot_2_sort_gallery_thumb.png
-      :img-alt: Sorting Widgets
+      :img-alt: BaseSorting Widgets
       :class-card: gallery-card
       :text-align: center
 
-   .. grid-item-card:: Waveforms Widgets
+   .. grid-item-card:: SortingAnalyzer Widgets
       :link-type: ref
       :link: sphx_glr_tutorials_widgets_plot_3_waveforms_gallery.py
       :img-top: /tutorials/widgets/images/thumb/sphx_glr_plot_3_waveforms_gallery_thumb.png
-      :img-alt: Waveforms Widgets
+      :img-alt: SortingAnalyzer Widgets
       :class-card: gallery-card
       :text-align: center
 
diff --git a/examples/how_to/read_various_formats.py b/examples/how_to/read_various_formats.py
index b1fe277d92..eb97177408 100644
--- a/examples/how_to/read_various_formats.py
+++ b/examples/how_to/read_various_formats.py
@@ -57,7 +57,7 @@
 print(isinstance(recording, si.BaseRecording))
 
 ##############################################################################
-# The :py:func:`~spikeinterface.extractors.read_spike2`` function is equivalent to instantiating a
+# The :py:func:`~spikeinterface.extractors.read_spike2` function is equivalent to instantiating a
 # :py:class:`~spikeinterface.extractors.Spike2RecordingExtractor` object:
 #
 
diff --git a/examples/tutorials/core/plot_1_recording_extractor.py b/examples/tutorials/core/plot_1_recording_extractor.py
index 477ba165b6..a3143161b2 100644
--- a/examples/tutorials/core/plot_1_recording_extractor.py
+++ b/examples/tutorials/core/plot_1_recording_extractor.py
@@ -75,16 +75,17 @@
 
 ##############################################################################
 # Some extractors also implement a :code:`write` function.
-
+from spikeinterface.core.binaryrecordingextractor import BinaryRecordingExtractor
 file_paths = ["traces0.raw", "traces1.raw"]
-se.BinaryRecordingExtractor.write_recording(recording, file_paths)
+
+BinaryRecordingExtractor.write_recording(recording, file_paths)
 
 ##############################################################################
 # We can read the written recording back with the proper extractor.
 # Note that this new recording is now "on disk" and not "in memory" as the Numpy recording was.
 # This means that the loading is "lazy" and the data are not loaded into memory.
 
-recording2 = se.BinaryRecordingExtractor(
+recording2 = BinaryRecordingExtractor(
     file_paths=file_paths, sampling_frequency=sampling_frequency, num_channels=num_channels, dtype=traces0.dtype
 )
 print(recording2)
diff --git a/examples/tutorials/core/plot_2_sorting_extractor.py b/examples/tutorials/core/plot_2_sorting_extractor.py
index b3ea82c77a..026547af28 100644
--- a/examples/tutorials/core/plot_2_sorting_extractor.py
+++ b/examples/tutorials/core/plot_2_sorting_extractor.py
@@ -57,14 +57,15 @@
 # Some extractors also implement a :code:`write` function. We can for example
 # save our newly created sorting object to NPZ format (a simple format based
 # on numpy used in :code:`spikeinterface`):
+from spikeinterface.core.npzsortingextractor import NpzSortingExtractor
 
 file_path = "my_sorting.npz"
-se.NpzSortingExtractor.write_sorting(sorting, file_path)
+NpzSortingExtractor.write_sorting(sorting, file_path)
 
 ##############################################################################
 # We can now read it back with the proper extractor:
 
-sorting2 = se.NpzSortingExtractor(file_path)
+sorting2 = NpzSortingExtractor(file_path)
 print(sorting2)
 
 ##############################################################################
diff --git a/examples/tutorials/extractors/README.rst b/examples/tutorials/extractors/README.rst
index fe705d4ff8..c147dbf20c 100644
--- a/examples/tutorials/extractors/README.rst
+++ b/examples/tutorials/extractors/README.rst
@@ -4,6 +4,6 @@ Extractors tutorials
 The :py:mod:`spikeinterface.extractors` module is designed to load and save recorded and sorted data and to handle
 probe information.
 
-- RecordingExtractors
-- SortingExtractors
+- Recordings
+- Sortings
 - Handling probe information
diff --git a/examples/tutorials/widgets/plot_1_rec_gallery.py b/examples/tutorials/widgets/plot_1_rec_gallery.py
index bb121e26a2..eab9eaba36 100644
--- a/examples/tutorials/widgets/plot_1_rec_gallery.py
+++ b/examples/tutorials/widgets/plot_1_rec_gallery.py
@@ -1,8 +1,8 @@
 """
-RecordingExtractor Widgets Gallery
-===================================
+BaseRecording Widgets Gallery
+=============================
 
-Here is a gallery of all the available widgets using RecordingExtractor objects.
+Here is a gallery of all the available widgets using BaseRecording objects.
 """
 
 import matplotlib.pyplot as plt
diff --git a/examples/tutorials/widgets/plot_3_waveforms_gallery.py b/examples/tutorials/widgets/plot_3_waveforms_gallery.py
index d2f4345d14..76041aab1a 100644
--- a/examples/tutorials/widgets/plot_3_waveforms_gallery.py
+++ b/examples/tutorials/widgets/plot_3_waveforms_gallery.py
@@ -1,8 +1,8 @@
 """
-Waveforms Widgets Gallery
-=========================
+SortingAnalyzer Widgets Gallery
+===============================
 
-Here is a gallery of all the available widgets using a pair of RecordingExtractor-SortingExtractor objects.
+Here is a gallery of all the available widgets using SortingAnalyzer objects.
 """
 
 import matplotlib.pyplot as plt
diff --git a/src/spikeinterface/core/__init__.py b/src/spikeinterface/core/__init__.py
index 9b9c411079..72222753f7 100644
--- a/src/spikeinterface/core/__init__.py
+++ b/src/spikeinterface/core/__init__.py
@@ -17,7 +17,7 @@
     NumpyEvent,
     NumpySnippets,
 )
-from .zarrextractors import ZarrRecordingExtractor, ZarrSortingExtractor, read_zarr, get_default_zarr_compressor
+from .zarrextractors import read_zarr, read_zarr_array, get_default_zarr_compressor
 from .binaryfolder import BinaryFolderRecording, read_binary_folder
 from .sortingfolder import NumpyFolderSorting, NpzFolderSorting, read_numpy_sorting_folder, read_npz_folder
 from .npysnippetsextractor import NpySnippetsExtractor, read_npy_snippets
diff --git a/src/spikeinterface/core/baserecording.py b/src/spikeinterface/core/baserecording.py
index 3ddefb53b8..772c026ccc 100644
--- a/src/spikeinterface/core/baserecording.py
+++ b/src/spikeinterface/core/baserecording.py
@@ -236,7 +236,6 @@ def get_traces(
         end_frame: int | None = None,
         channel_ids: list | np.ndarray | tuple | None = None,
         order: Literal["C", "F"] | None = None,
-        return_scaled: bool | None = None,
         return_in_uV: bool = False,
     ) -> np.ndarray:
         """Returns traces from recording.
@@ -253,10 +252,6 @@ def get_traces(
             The channel ids. If None, all channels are used, default: None
         order : "C" | "F" | None, default: None
             The order of the traces ("C" | "F"). If None, traces are returned as they are
-        return_scaled : bool | None, default: None
-            DEPRECATED. Use return_in_uV instead.
-            If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
-            traces are scaled to uV
         return_in_uV : bool, default: False
             If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
             traces are scaled to uV
@@ -282,15 +277,6 @@ def get_traces(
             assert order in ["C", "F"]
             traces = np.asanyarray(traces, order=order)
 
-        # Handle deprecated return_scaled parameter
-        if return_scaled is not None:
-            warnings.warn(
-                "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-                category=FutureWarning,
-                stacklevel=2,
-            )
-            return_in_uV = return_scaled
-
         if return_in_uV:
             if not self.has_scaleable_traces():
                 if self._dtype.kind == "f":
@@ -331,6 +317,7 @@ def save(self, format="binary", verbose: bool = False, **save_kwargs):
         ----------
         format : str, default: "binary"
             The format to save the recording in. Options are:
+
             - "binary": Saves the recording in binary format.
             - "zarr": Saves the recording in Zarr format.
             - "memory": Saves the recording in memory (shared memory or numpy array).
@@ -365,13 +352,17 @@ def save(self, format="binary", verbose: bool = False, **save_kwargs):
                     Global filters for zarr (global)
                 - compressor_by_dataset: dict or None, default: None
                     Optional compressor per dataset:
+
                         - traces
                         - times
+
                     If None, the global compressor is used
                 - filters_by_dataset: dict or None, default: None
                     Optional filters per dataset:
+
                         - traces
                         - times
+
                     If None, the global filters are used
             * "memory" format:
                 - sharedmem : bool, default: True
diff --git a/src/spikeinterface/core/basesnippets.py b/src/spikeinterface/core/basesnippets.py
index 5b38c47791..7678f0323b 100644
--- a/src/spikeinterface/core/basesnippets.py
+++ b/src/spikeinterface/core/basesnippets.py
@@ -93,7 +93,6 @@ def get_snippets(
         indices=None,
         segment_index: int | None = None,
         channel_ids: list | None = None,
-        return_scaled: bool | None = None,
         return_in_uV: bool = False,
     ):
         """
@@ -107,10 +106,6 @@ def get_snippets(
             The segment index to get snippets from. If snippets is multi-segment, it is required.
         channel_ids : list | None, default: None
             The channel ids. If None, all channels are used.
-        return_scaled : bool | None, default: None
-            DEPRECATED. Use return_in_uV instead.
-            If True and the snippets has scaling (gain_to_uV and offset_to_uV properties),
-            snippets are scaled to uV
         return_in_uV : bool, default: False
             If True and the snippets has scaling (gain_to_uV and offset_to_uV properties),
             snippets are scaled to uV
@@ -125,15 +120,6 @@ def get_snippets(
         channel_indices = self.ids_to_indices(channel_ids, prefer_slice=True)
         wfs = spts.get_snippets(indices, channel_indices=channel_indices)
 
-        # Handle deprecated return_scaled parameter
-        if return_scaled is not None:
-            warn(
-                "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-                category=FutureWarning,
-                stacklevel=2,
-            )
-            return_in_uV = return_scaled
-
         if return_in_uV:
             if not self.has_scaleable_traces():
                 raise ValueError(
@@ -153,7 +139,6 @@ def get_snippets_from_frames(
         start_frame: int | None = None,
         end_frame: int | None = None,
         channel_ids: list | None = None,
-        return_scaled: bool | None = None,
         return_in_uV: bool = False,
     ):
         """
@@ -169,10 +154,6 @@ def get_snippets_from_frames(
             The end frame. If None, the number of samples in the segment is used.
         channel_ids : list | None, default: None
             The channel ids. If None, all channels are used.
-        return_scaled : bool | None, default: None
-            DEPRECATED. Use return_in_uV instead.
-            If True and the snippets has scaling (gain_to_uV and offset_to_uV properties),
-            snippets are scaled to uV
         return_in_uV : bool, default: False
             If True and the snippets has scaling (gain_to_uV and offset_to_uV properties),
             snippets are scaled to uV
@@ -186,15 +167,6 @@ def get_snippets_from_frames(
         spts = self._snippets_segments[segment_index]
         indices = spts.frames_to_indices(start_frame, end_frame)
 
-        # Handle deprecated return_scaled parameter
-        if return_scaled is not None:
-            warn(
-                "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-                category=FutureWarning,
-                stacklevel=2,
-            )
-            return_in_uV = return_scaled
-
         return self.get_snippets(indices, channel_ids=channel_ids, return_in_uV=return_in_uV)
 
     def select_channels(self, channel_ids: list | np.ndarray | tuple) -> "BaseSnippets":
diff --git a/src/spikeinterface/core/basesorting.py b/src/spikeinterface/core/basesorting.py
index 79e07d8cb4..1e136f2dff 100644
--- a/src/spikeinterface/core/basesorting.py
+++ b/src/spikeinterface/core/basesorting.py
@@ -522,6 +522,7 @@ def save(self, format="numpy_folder", **save_kwargs):
         ----------
         format : str, default: "numpy_folder"
             The format to save the sorting in. Options are:
+
             - "numpy_folder": Saves the sorting in a binary numpy folder format.
             - "zarr": Saves the sorting in Zarr format.
             - "memory": Saves the sorting in memory (shared memory or numpy array).
@@ -1024,7 +1025,7 @@ def to_spike_vector(
             warnings.warn(
                 "Sorting.to_spike_vector() with extremum_channel_inds is deprecated. "
                 "Use main_channel_indices instead"
-                "This will be removed in 0.016.0"
+                "This will be removed in 0.106.0"
             )
             main_channel_indices = np.array([extremum_channel_inds[unit_id] for unit_id in self.unit_ids])
 
diff --git a/src/spikeinterface/core/channelsaggregationrecording.py b/src/spikeinterface/core/channelsaggregationrecording.py
index bd60602754..ae7309d1ab 100644
--- a/src/spikeinterface/core/channelsaggregationrecording.py
+++ b/src/spikeinterface/core/channelsaggregationrecording.py
@@ -15,18 +15,16 @@ class ChannelsAggregationRecording(BaseRecording):
 
     Do not use this class directly but use `si.aggregate_channels(...)`
 
-    """
-
-    def __init__(self, recording_list_or_dict=None, renamed_channel_ids=None, recording_list=None):
+    Parameters
+    ----------
+    recording_list_or_dict : list or dict
+        The list or dictionary of recordings to aggregate.
+    renamed_channel_ids : list, optional
+        The new channel ids for the aggregated recording. If None, default unique consecutive ids are used.
 
-        if recording_list is not None:
-            warnings.warn(
-                "`recording_list` is deprecated and will be removed in 0.105.0. Please use `recording_list_or_dict` instead.",
-                category=FutureWarning,
-                stacklevel=2,
-            )
-            recording_list_or_dict = recording_list
+    """
 
+    def __init__(self, recording_list_or_dict=None, renamed_channel_ids=None):
         if isinstance(recording_list_or_dict, dict):
             recording_list = list(recording_list_or_dict.values())
             recording_ids = list(recording_list_or_dict.keys())
@@ -149,7 +147,20 @@ def __init__(self, recording_list_or_dict=None, renamed_channel_ids=None, record
             sub_segment = ChannelsAggregationRecordingSegment(channel_map, parent_segments)
             self.add_recording_segment(sub_segment)
 
-        self._kwargs = {"recording_list": recording_list, "renamed_channel_ids": renamed_channel_ids}
+        self._kwargs = {"recording_list_or_dict": recording_list, "renamed_channel_ids": renamed_channel_ids}
+
+    @classmethod
+    def _handle_kwargs_backward_compatibility(cls, old_kwargs, full_dict):
+        """
+        Fix backward compatibility issues with `recording_list' argument,
+        which is renamed to `recording_list_or_dict'.
+        """
+        if "recording_list" in old_kwargs:
+            new_kwargs = old_kwargs.copy()
+            new_kwargs["recording_list_or_dict"] = new_kwargs.pop("recording_list")
+        else:
+            new_kwargs = old_kwargs
+        return new_kwargs
 
     @property
     def recordings(self):
@@ -258,7 +269,6 @@ def get_traces(
 def aggregate_channels(
     recording_list_or_dict=None,
     renamed_channel_ids=None,
-    recording_list=None,
 ):
     """
     Aggregates channels of multiple recording into a single recording object
@@ -282,4 +292,4 @@ def aggregate_channels(
     values, are dropped.
     """
 
-    return ChannelsAggregationRecording(recording_list_or_dict, renamed_channel_ids, recording_list)
+    return ChannelsAggregationRecording(recording_list_or_dict, renamed_channel_ids)
diff --git a/src/spikeinterface/core/job_tools.py b/src/spikeinterface/core/job_tools.py
index 737fc1c668..59af6fd254 100644
--- a/src/spikeinterface/core/job_tools.py
+++ b/src/spikeinterface/core/job_tools.py
@@ -21,7 +21,9 @@
 )
 
 _shared_job_kwargs_doc = """**job_kwargs : keyword arguments for parallel processing:
+
     * chunk_duration or chunk_size or chunk_memory or total_memory
+
         - chunk_size : int
             Number of samples per chunk
         - chunk_memory : str
@@ -30,12 +32,15 @@
             Total memory usage (e.g. "500M", "2G")
         - chunk_duration : str or float or None
             Chunk duration in s if float or with units if str (e.g. "1s", "500ms")
+
     * n_jobs : int | float
         Number of workers that will be requested during multiprocessing. Note that
         the OS determines how this is distributed, but for convenience one can use
+
         * -1 the number of workers is the same as the number of cores available to this
           process, respecting CPU affinity restrictions where possible
         * float between 0 and 1 uses a fraction of that core count
+
     * progress_bar : bool
         If True, a progress bar is printed
     * mp_context : "fork" | "spawn" | None, default: None
diff --git a/src/spikeinterface/core/recording_tools.py b/src/spikeinterface/core/recording_tools.py
index b20b543538..09d0ce0deb 100644
--- a/src/spikeinterface/core/recording_tools.py
+++ b/src/spikeinterface/core/recording_tools.py
@@ -264,7 +264,6 @@ def write_to_h5_dataset_format(
     chunk_size=None,
     chunk_memory="500M",
     verbose=False,
-    return_scaled=None,
     return_in_uV=False,
 ):
     """
@@ -297,8 +296,6 @@ def write_to_h5_dataset_format(
         Chunk size in bytes must end with "k", "M" or "G"
     verbose : bool, default: False
         If True, output is verbose (when chunks are used)
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: False
         If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
         traces are dumped to uV
@@ -340,14 +337,6 @@ def write_to_h5_dataset_format(
     chunk_size = ensure_chunk_size(recording, chunk_size=chunk_size, chunk_memory=chunk_memory, n_jobs=1)
 
     if chunk_size is None:
-        # Handle deprecated return_scaled parameter
-        if return_scaled is not None:
-            warnings.warn(
-                "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-                category=FutureWarning,
-            )
-            return_in_uV = return_scaled
-
         traces = recording.get_traces(return_in_uV=return_in_uV)
         if dtype is not None:
             traces = traces.astype(dtype_file, copy=False)
@@ -392,9 +381,7 @@ def write_to_h5_dataset_format(
     return save_path
 
 
-def get_random_data_chunks(
-    recording, return_scaled=None, return_in_uV=False, concatenated=True, **random_slices_kwargs
-):
+def get_random_data_chunks(recording, return_in_uV=False, concatenated=True, **random_slices_kwargs):
     """
     Extract random chunks across segments.
 
@@ -408,8 +395,6 @@ def get_random_data_chunks(
     ----------
     recording : BaseRecording
         The recording to get random chunks from
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: False
         If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
         traces are scaled to uV
@@ -426,15 +411,6 @@ def get_random_data_chunks(
     chunk_list : np.ndarray | list of np.array
         Array of concatenate chunks per segment
     """
-    # Handle deprecated return_scaled parameter
-    if return_scaled is not None:
-        warnings.warn(
-            "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-            category=FutureWarning,
-            stacklevel=2,
-        )
-        return_in_uV = return_scaled
-
     return get_chunks(
         recording,
         concatenated=concatenated,
@@ -525,7 +501,6 @@ def _noise_level_chunk_init(recording, return_in_uV, method):
 
 def get_noise_levels(
     recording: "BaseRecording",
-    return_scaled: bool | None = None,
     return_in_uV: bool = True,
     method: Literal["mad", "std", "rms"] = "mad",
     force_recompute: bool = False,
@@ -548,8 +523,6 @@ def get_noise_levels(
 
     recording : BaseRecording
         The recording extractor to get noise levels
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: True
         If True, returned noise levels are scaled to uV
     method : "mad" | "std" | "rms", default: "mad"
@@ -567,15 +540,6 @@ def get_noise_levels(
     noise_levels : array
         Noise levels for each channel
     """
-
-    # Handle deprecated return_scaled parameter
-    if return_scaled is not None:
-        warnings.warn(
-            "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-            category=FutureWarning,
-        )
-        return_in_uV = return_scaled
-
     if return_in_uV:
         key = f"noise_level_{method}_scaled"
     else:
diff --git a/src/spikeinterface/core/sortinganalyzer.py b/src/spikeinterface/core/sortinganalyzer.py
index 50c226e11a..3e80b9fab4 100644
--- a/src/spikeinterface/core/sortinganalyzer.py
+++ b/src/spikeinterface/core/sortinganalyzer.py
@@ -62,7 +62,6 @@ def create_sorting_analyzer(
     sparse: bool = True,
     sparsity: ChannelSparsity | None = None,
     set_sparsity_by_dict_key: bool = False,
-    return_scaled: bool | None = None,
     return_in_uV: bool = True,
     overwrite: bool = False,
     backend_options: dict[str, Any] | None = None,
@@ -119,14 +118,9 @@ def create_sorting_analyzer(
     set_sparsity_by_dict_key : bool, default: False
         If True and passing recording and sorting dicts, will set the sparsity based on the dict keys,
         and other `sparsity_kwargs` are overwritten. If False, use other sparsity settings.
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
-        All extensions that play with traces will use this global return_in_uV : "waveforms", "noise_levels", "templates".
-        This prevent return_in_uV being differents from different extensions and having wrong snr for instance.
-    return_in_uV : bool, default: None
+    return_in_uV : bool, default: True
         If True, all extensions that play with traces will use this global return_in_uV : "waveforms", "noise_levels", "templates".
         This prevent return_in_uV being differents from different extensions and having wrong snr for instance.
-        If None, use return_scaled value.
     overwrite: bool, default: False
         If True, overwrite the folder if it already exists.
     backend_options : dict | None, default: None
@@ -270,7 +264,6 @@ def create_sorting_analyzer(
             sparse=sparse,
             sparsity=sparsity,
             main_channel_indices=main_channel_indices,
-            return_scaled=return_scaled,
             return_in_uV=return_in_uV,
             overwrite=overwrite,
             backend_options=backend_options,
@@ -330,15 +323,6 @@ def create_sorting_analyzer(
     else:
         sparsity = None
 
-    # Handle deprecated return_scaled parameter
-    if return_scaled is not None:
-        warnings.warn(
-            "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-            category=FutureWarning,
-            stacklevel=2,
-        )
-        return_in_uV = return_scaled if return_in_uV is None else return_in_uV
-
     # Handle return_in_uV parameter for recordings without scaling
     if return_in_uV and not recording.has_scaleable_traces() and recording.get_dtype().kind == "i":
         warnings.warn("create_sorting_analyzer: recording does not have scaling to uV, forcing return_in_uV=False")
@@ -452,9 +436,6 @@ def __init__(
         self.peak_sign = peak_sign
         self.peak_mode = peak_mode
         self._main_channel_indices = None
-
-        # For backward compatibility
-        self.return_scaled = return_in_uV
         self.folder: str | Path | None = None
 
         # this is used to store temporary recording
@@ -539,7 +520,6 @@ def create(
         folder: str | Path | None = None,
         lazy: bool = False,
         sparsity: ChannelSparsity | None = None,
-        return_scaled: bool | None = None,
         return_in_uV: bool = True,
         peak_sign: PeakSignType = "both",
         peak_mode: PeakModeType = "extremum",
@@ -549,13 +529,6 @@ def create(
         assert (
             main_channel_indices is not None
         ), "To create a SortingAnalyzer you need to specify the main_channel_indices"
-        if return_scaled is not None:
-            warnings.warn(
-                "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-                category=FutureWarning,
-                stacklevel=2,
-            )
-            return_in_uV = return_scaled if return_in_uV is None else return_in_uV
 
         # some checks
         if sorting.sampling_frequency != recording.sampling_frequency:
@@ -2816,8 +2789,8 @@ def get_metrics_extension_data(self):
         metrics_df : pandas.DataFrame
             A concatenated dataframe with all available metrics.
 
-        Note
-        ----
+        Notes
+        -----
         Duplicated columns are removed (can happen if several metric extensions have a metric with the same name).
         """
         import pandas as pd
diff --git a/src/spikeinterface/core/testing.py b/src/spikeinterface/core/testing.py
index 2feee7792e..6ad7458c37 100644
--- a/src/spikeinterface/core/testing.py
+++ b/src/spikeinterface/core/testing.py
@@ -14,7 +14,6 @@ def check_sorted_arrays_equal(a1, a2):
 def check_recordings_equal(
     RX1: BaseRecording,
     RX2: BaseRecording,
-    return_scaled=None,
     return_in_uV=True,
     force_dtype=None,
     check_annotations: bool = False,
@@ -29,9 +28,6 @@ def check_recordings_equal(
         First recording
     RX2 : BaseRecording
         Second recording
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
-        If True, compare scaled traces
     return_in_uV : bool, default: True
         If True, compare scaled traces.
     force_dtype : dtype, default: None
@@ -41,14 +37,6 @@ def check_recordings_equal(
     check_properties : bool, default: False
         If True, check properties
     """
-    # Handle deprecated return_scaled parameter
-    if return_scaled is not None:
-        warnings.warn(
-            "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-            category=FutureWarning,
-            stacklevel=2,
-        )
-        return_in_uV = return_scaled
     assert RX1.get_num_segments() == RX2.get_num_segments()
 
     for segment_idx in range(RX1.get_num_segments()):
diff --git a/src/spikeinterface/core/tests/test_baserecording.py b/src/spikeinterface/core/tests/test_baserecording.py
index 809df7abbe..63fe18f899 100644
--- a/src/spikeinterface/core/tests/test_baserecording.py
+++ b/src/spikeinterface/core/tests/test_baserecording.py
@@ -288,8 +288,6 @@ def test_BaseRecording(create_cache_folder):
     assert traces_int16.dtype == "int16"
 
     # Both return_scaled and return_in_uV raise error when no gain_to_uV/offset_to_uV properties
-    with pytest.raises(ValueError):
-        traces_float32 = rec_int16.get_traces(return_scaled=True)
     with pytest.raises(ValueError):
         traces_float32 = rec_int16.get_traces(return_in_uV=True)
 
@@ -297,17 +295,9 @@ def test_BaseRecording(create_cache_folder):
     rec_int16.set_property("gain_to_uV", [0.195] * 5)
     rec_int16.set_property("offset_to_uV", [0.0] * 5)
 
-    # Test deprecated return_scaled parameter
-    with pytest.warns(FutureWarning, match="`return_scaled` is deprecated"):
-        traces_float32_old = rec_int16.get_traces(return_scaled=True)  # Keep this for testing the deprecation warning
-        assert traces_float32_old.dtype == "float32"
-
     # Test new return_in_uV parameter
-    traces_float32_new = rec_int16.get_traces(return_in_uV=True)
-    assert traces_float32_new.dtype == "float32"
-
-    # Verify both parameters produce the same result
-    assert np.array_equal(traces_float32_old, traces_float32_new)
+    traces_float32 = rec_int16.get_traces(return_in_uV=True)
+    assert traces_float32.dtype == "float32"
 
     # test cast with dtype
     rec_float32 = rec_int16.astype("float32")
diff --git a/src/spikeinterface/core/tests/test_zarrextractors.py b/src/spikeinterface/core/tests/test_zarrextractors.py
index 7e58898a6e..6278541698 100644
--- a/src/spikeinterface/core/tests/test_zarrextractors.py
+++ b/src/spikeinterface/core/tests/test_zarrextractors.py
@@ -4,13 +4,16 @@
 import zarr
 
 from spikeinterface.core import (
-    ZarrRecordingExtractor,
-    ZarrSortingExtractor,
     generate_recording,
     generate_sorting,
     load,
 )
-from spikeinterface.core.zarrextractors import add_sorting_to_zarr_group, get_default_zarr_compressor
+from spikeinterface.core.zarrextractors import (
+    ZarrRecordingExtractor,
+    ZarrSortingExtractor,
+    add_sorting_to_zarr_group,
+    get_default_zarr_compressor,
+)
 
 
 def test_zarr_compression_options(tmp_path):
diff --git a/src/spikeinterface/core/time_series_tools.py b/src/spikeinterface/core/time_series_tools.py
index 44b6925bb5..758482b965 100644
--- a/src/spikeinterface/core/time_series_tools.py
+++ b/src/spikeinterface/core/time_series_tools.py
@@ -562,8 +562,6 @@ def get_chunks(time_series: TimeSeries, concatenated=True, get_data_kwargs=None,
     ----------
     time_series : TimeSeries
         The time_series object to get random chunks from
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: False
         If True and the time_series has scaling (gain_to_uV and offset_to_uV properties),
         traces are scaled to uV
diff --git a/src/spikeinterface/core/waveform_tools.py b/src/spikeinterface/core/waveform_tools.py
index 942d1b9cb4..9fedc89324 100644
--- a/src/spikeinterface/core/waveform_tools.py
+++ b/src/spikeinterface/core/waveform_tools.py
@@ -29,7 +29,6 @@ def extract_waveforms_to_buffers(
     nbefore,
     nafter,
     mode="memmap",
-    return_scaled=None,
     return_in_uV=True,
     folder=None,
     dtype=None,
@@ -62,8 +61,6 @@ def extract_waveforms_to_buffers(
         N samples after spike
     mode: "memmap" | "shared_memory", default: "memmap"
         The mode to use for the buffer
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: True
         If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
         traces are scaled to uV
@@ -89,15 +86,6 @@ def extract_waveforms_to_buffers(
         Optionally return in case of shared_memory if copy=False.
         Dictionary to "construct" array in workers process (memmap file or sharemem info)
     """
-    # Handle deprecated return_scaled parameter
-    if return_scaled is not None:
-        warnings.warn(
-            "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-            category=FutureWarning,
-            stacklevel=2,
-        )
-        return_in_uV = return_scaled
-
     job_kwargs = fix_job_kwargs(job_kwargs)
 
     if dtype is None:
@@ -425,7 +413,6 @@ def extract_waveforms_to_single_buffer(
     nbefore,
     nafter,
     mode="memmap",
-    return_scaled=None,
     return_in_uV=True,
     file_path=None,
     dtype=None,
@@ -467,8 +454,6 @@ def extract_waveforms_to_single_buffer(
         N samples after spike
     mode: "memmap" | "shared_memory", default: "memmap"
         The mode to use for the buffer
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: False
         If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
         traces are scaled to uV
@@ -497,16 +482,6 @@ def extract_waveforms_to_single_buffer(
         Optionally return in case of shared_memory if copy=False.
         Dictionary to "construct" array in workers process (memmap file or sharemem info)
     """
-
-    # Handle deprecated return_scaled parameter
-    if return_scaled is not None:
-        warnings.warn(
-            "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-            category=FutureWarning,
-            stacklevel=2,
-        )
-        return_in_uV = return_scaled
-
     n_samples = nbefore + nafter
 
     if dtype is None:
@@ -755,7 +730,6 @@ def estimate_templates(
     nbefore: int,
     nafter: int,
     operator: str = "average",
-    return_scaled=None,
     return_in_uV=True,
     sparsity_mask=None,
     job_name=None,
@@ -773,14 +747,12 @@ def estimate_templates(
     spikes: 1d numpy array with several fields
         Spikes handled as a unique vector.
         This vector can be obtained with: `spikes = sorting.to_spike_vector()`
-    unit_ids: list ot numpy
+    unit_ids: list or numpy.ndarray
         List of unit_ids
     nbefore: int
         Number of samples to cut out before a spike
     nafter: int
         Number of samples to cut out after a spike
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: True
         If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
         traces are scaled to uV
@@ -793,15 +765,6 @@ def estimate_templates(
         The average templates with shape (num_units, nbefore + nafter, num_channels)
 
     """
-    # Handle deprecated return_scaled parameter
-    if return_scaled is not None:
-        warnings.warn(
-            "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-            category=FutureWarning,
-            stacklevel=2,
-        )
-        return_in_uV = return_scaled
-
     if job_name is None:
         job_name = "estimate_templates"
 
@@ -854,7 +817,6 @@ def estimate_templates_with_accumulator(
     unit_ids: list | np.ndarray,
     nbefore: int,
     nafter: int,
-    return_scaled=None,
     return_in_uV=True,
     sparsity_mask=None,
     job_name=None,
@@ -883,8 +845,6 @@ def estimate_templates_with_accumulator(
         Number of samples to cut out before a spike
     nafter: int
         Number of samples to cut out after a spike
-    return_scaled : bool | None, default: None
-        DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: True
         If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
         traces are scaled to uV
@@ -898,16 +858,6 @@ def estimate_templates_with_accumulator(
     templates_array: np.array
         The average templates with shape (num_units, nbefore + nafter, num_channels)
     """
-
-    # Handle deprecated return_scaled parameter
-    if return_scaled is not None:
-        warnings.warn(
-            "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-            category=FutureWarning,
-            stacklevel=2,
-        )
-        return_in_uV = return_scaled
-
     job_kwargs = fix_job_kwargs(job_kwargs)
     num_worker = job_kwargs["n_jobs"]
 
diff --git a/src/spikeinterface/curation/__init__.py b/src/spikeinterface/curation/__init__.py
index 9d3405ef62..9dff51dcac 100644
--- a/src/spikeinterface/curation/__init__.py
+++ b/src/spikeinterface/curation/__init__.py
@@ -6,7 +6,6 @@
 from .auto_merge import (
     compute_merge_unit_groups,
     auto_merge_units,
-    get_potential_auto_merge,
 )
 
 # manual sorting,
diff --git a/src/spikeinterface/curation/auto_merge.py b/src/spikeinterface/curation/auto_merge.py
index 566d88023f..a31b841882 100644
--- a/src/spikeinterface/curation/auto_merge.py
+++ b/src/spikeinterface/curation/auto_merge.py
@@ -525,199 +525,6 @@ def _auto_merge_units_single_iteration(
         return merged_analyzer
 
 
-def get_potential_auto_merge(
-    sorting_analyzer: SortingAnalyzer,
-    preset: str | None = "similarity_correlograms",
-    resolve_graph: bool = False,
-    min_spikes: int = 100,
-    min_snr: float = 2,
-    max_distance_um: float = 150.0,
-    corr_diff_thresh: float = 0.16,
-    template_diff_thresh: float = 0.25,
-    contamination_thresh: float = 0.2,
-    presence_distance_thresh: float = 100.0,
-    p_value: float = 0.2,
-    cc_thresh: float = 0.1,
-    censored_period_ms: float = 0.3,
-    refractory_period_ms: float = 1.0,
-    sigma_smooth_ms: float = 0.6,
-    adaptative_window_thresh: float = 0.5,
-    censor_correlograms_ms: float = 0.15,
-    firing_contamination_balance: float = 1.5,
-    k_nn: int = 10,
-    knn_kwargs: dict | None = None,
-    presence_distance_kwargs: dict | None = None,
-    extra_outputs: bool = False,
-    steps: list[str] | None = None,
-) -> list[tuple[int | str, int | str]] | Tuple[tuple[int | str, int | str], dict]:
-    """
-    This function is deprecated. Use compute_merge_unit_groups() instead.
-    This will be removed in 0.103.0
-
-    Algorithm to find and check potential merges between units.
-
-    The merges are proposed based on a series of steps with different criteria:
-
-        * "num_spikes": enough spikes are found in each unit for computing the correlogram (`min_spikes`)
-        * "snr": the SNR of the units is above a threshold (`min_snr`)
-        * "remove_contaminated": each unit is not contaminated (by checking auto-correlogram - `contamination_thresh`)
-        * "unit_locations": estimated unit locations are close enough (`max_distance_um`)
-        * "correlogram": the cross-correlograms of the two units are similar to each auto-corrleogram (`corr_diff_thresh`)
-        * "template_similarity": the templates of the two units are similar (`template_diff_thresh`)
-        * "presence_distance": the presence of the units is complementary in time (`presence_distance_thresh`)
-        * "cross_contamination": the cross-contamination is not significant (`cc_thresh` and `p_value`)
-        * "knn": the two units are close in the feature space
-        * "quality_score": the unit "quality score" is increased after the merge
-        * "slay_score":  a combined score, factoring in a template similarity measure, a cross-correlation significance measure and a sliding refractory period violation measure, based on the SLAy algorithm.
-
-    The "quality score" factors in the increase in firing rate (**f**) due to the merge and a possible increase in
-    contamination (**C**), wheighted by a factor **k** (`firing_contamination_balance`).
-
-    .. math::
-
-        Q = f(1 - (k + 1)C)
-
-    IMPORTANT: internally, all computations are relying on extensions of the analyzer, that are computed
-    with default parameters if not present (i.e. correlograms, template_similarity, ...) If you want to
-    have a finer control on these values, please precompute the extensions before applying the auto_merge
-
-    Parameters
-    ----------
-    sorting_analyzer : SortingAnalyzer
-        The SortingAnalyzer
-    preset : "similarity_correlograms" | "x_contaminations" | "temporal_splits" | "feature_neighbors" | "slay" | None, default: "similarity_correlograms"
-        The preset to use for the auto-merge. Presets combine different steps into a recipe and focus on:
-
-        * | "similarity_correlograms": mainly focused on template similarity and correlograms.
-          | It uses the following steps: "num_spikes", "remove_contaminated", "unit_locations",
-          | "template_similarity", "correlogram", "quality_score"
-        * | "x_contaminations": similar to "similarity_correlograms", but checks for cross-contamination instead of correlograms.
-          | It uses the following steps: "num_spikes", "remove_contaminated", "unit_locations",
-          | "template_similarity", "cross_contamination", "quality_score"
-        * | "temporal_splits": focused on finding temporal splits using presence distance.
-          | It uses the following steps: "num_spikes", "remove_contaminated", "unit_locations",
-          | "template_similarity", "presence_distance", "quality_score"
-        * | "feature_neighbors": focused on finding unit pairs whose spikes are close in the feature space using kNN.
-          | It uses the following steps: "num_spikes", "snr", "remove_contaminated", "unit_locations",
-          | "knn", "quality_score"
-        * | "slay": an approximate implementation of SLAy, original implementation at https://github.com/saikoukunt/SLAy.
-          | The spikeinterface version uses `template_similarity`, rather than an auto-encoder.
-          | It uses the following steps: "template_similarity", "slay_score"
-
-        If `preset` is None, you can specify the steps manually with the `steps` parameter.
-    resolve_graph : bool, default: False
-        If True, the function resolves the potential unit pairs to be merged into multiple-unit merges.
-    min_spikes : int, default: 100
-        Minimum number of spikes for each unit to consider a potential merge.
-        Enough spikes are needed to estimate the correlogram
-    min_snr : float, default 2
-        Minimum Signal to Noise ratio for templates to be considered while merging
-    max_distance_um : float, default: 150
-        Maximum distance between units for considering a merge
-    corr_diff_thresh : float, default: 0.16
-        The threshold on the "correlogram distance metric" for considering a merge.
-        It needs to be between 0 and 1
-    template_diff_thresh : float, default: 0.25
-        The threshold on the "template distance metric" for considering a merge.
-        It needs to be between 0 and 1
-    contamination_thresh : float, default: 0.2
-        Threshold for not taking in account a unit when it is too contaminated.
-    presence_distance_thresh : float, default: 100
-        Parameter to control how present two units should be simultaneously.
-    p_value : float, default: 0.2
-        The p-value threshold for the cross-contamination test.
-    cc_thresh : float, default: 0.1
-        The threshold on the cross-contamination for considering a merge.
-    censored_period_ms : float, default: 0.3
-        Used to compute the refractory period violations aka "contamination".
-    refractory_period_ms : float, default: 1
-        Used to compute the refractory period violations aka "contamination".
-    sigma_smooth_ms : float, default: 0.6
-        Parameters to smooth the correlogram estimation.
-    adaptative_window_thresh : float, default: 0.5
-        Parameter to detect the window size in correlogram estimation.
-    censor_correlograms_ms : float, default: 0.15
-        The period to censor on the auto and cross-correlograms.
-    firing_contamination_balance : float, default: 1.5
-        Parameter to control the balance between firing rate and contamination in computing unit "quality score".
-    k_nn : int, default 5
-        The number of neighbors to consider for every spike in the recording.
-    knn_kwargs : dict, default None
-        The dict of extra params to be passed to knn.
-    extra_outputs : bool, default: False
-        If True, an additional dictionary (`outs`) with processed data is returned.
-    steps : None or list of str, default: None
-        Which steps to run, if no preset is used.
-        Pontential steps : "num_spikes", "snr", "remove_contaminated", "unit_locations", "correlogram",
-        "template_similarity", "presence_distance", "cross_contamination", "knn", "quality_score"
-        Please check steps explanations above!
-    presence_distance_kwargs : None|dict, default: None
-        A dictionary of kwargs to be passed to compute_presence_distance().
-
-    Returns
-    -------
-    potential_merges:
-        A list of tuples of 2 elements (if `resolve_graph`if false) or 2+ elements (if `resolve_graph` is true).
-        List of pairs that could be merged.
-    outs:
-        Returned only when extra_outputs=True
-        A dictionary that contains data for debugging and plotting.
-
-    References
-    ----------
-    This function is inspired and built upon similar functions from Lussac [Llobet]_,
-    done by Aurelien Wyngaard and Victor Llobet.
-    https://github.com/BarbourLab/lussac/blob/v1.0.0/postprocessing/merge_units.py
-    """
-    # deprecation moved to 0.105.0 for @zm711
-    warnings.warn(
-        "get_potential_auto_merge() is deprecated and will be removed in version 0.105.0. Use compute_merge_unit_groups() instead",
-        FutureWarning,
-        stacklevel=2,
-    )
-
-    presence_distance_kwargs = presence_distance_kwargs or dict()
-    knn_kwargs = knn_kwargs or dict()
-    return compute_merge_unit_groups(
-        sorting_analyzer,
-        preset,
-        resolve_graph,
-        steps_params={
-            "num_spikes": {"min_spikes": min_spikes},
-            "snr": {"min_snr": min_snr},
-            "remove_contaminated": {
-                "contamination_thresh": contamination_thresh,
-                "refractory_period_ms": refractory_period_ms,
-                "censored_period_ms": censored_period_ms,
-            },
-            "unit_locations": {"max_distance_um": max_distance_um},
-            "correlogram": {
-                "corr_diff_thresh": corr_diff_thresh,
-                "censor_correlograms_ms": censor_correlograms_ms,
-                "sigma_smooth_ms": sigma_smooth_ms,
-                "adaptative_window_thresh": adaptative_window_thresh,
-            },
-            "template_similarity": {"template_diff_thresh": template_diff_thresh},
-            "presence_distance": {"presence_distance_thresh": presence_distance_thresh, **presence_distance_kwargs},
-            "knn": {"k_nn": k_nn, **knn_kwargs},
-            "cross_contamination": {
-                "cc_thresh": cc_thresh,
-                "p_value": p_value,
-                "refractory_period_ms": refractory_period_ms,
-                "censored_period_ms": censored_period_ms,
-            },
-            "quality_score": {
-                "firing_contamination_balance": firing_contamination_balance,
-                "refractory_period_ms": refractory_period_ms,
-                "censored_period_ms": censored_period_ms,
-            },
-        },
-        compute_needed_extensions=True,
-        extra_outputs=extra_outputs,
-        steps=steps,
-    )
-
-
 def auto_merge_units(
     sorting_analyzer: SortingAnalyzer,
     presets: list | None = ["similarity_correlograms"],
diff --git a/src/spikeinterface/curation/curation_model.py b/src/spikeinterface/curation/curation_model.py
index adff9d73d6..128bc0e6ba 100644
--- a/src/spikeinterface/curation/curation_model.py
+++ b/src/spikeinterface/curation/curation_model.py
@@ -479,15 +479,6 @@ def validate_curation_dict(self):
         return self
 
 
-def CurationModel(*args, **kwargs):
-    warnings.warn(
-        "`CurationModel` is deprecated and will be removed in 0.105.0. Use `Curation` instead",
-        FutureWarning,
-        stacklevel=2,
-    )
-    return Curation(*args, **kwargs)
-
-
 class SequentialCuration(BaseModel):
     """
     A Pydantic model which defines a sequence of curation steps. If using sequential curations,
diff --git a/src/spikeinterface/extractors/__init__.py b/src/spikeinterface/extractors/__init__.py
index 75879528bb..3bce7907e4 100644
--- a/src/spikeinterface/extractors/__init__.py
+++ b/src/spikeinterface/extractors/__init__.py
@@ -5,59 +5,3 @@
 
 from .neoextractors import get_neo_num_blocks, get_neo_streams
 from .phykilosortextractors import read_kilosort_as_analyzer
-
-from warnings import warn
-
-
-# deprecation of class import idea from neuroconv
-# this __getattr__ is only triggered if the normal lookup fails so import
-# any of our functions is fine but if someone tries to import a class this raises
-# the warning and then returns the "function" version which will look the same
-# to the end-user
-# to be removed after version 0.105.0
-def __getattr__(extractor_name):
-    # we need this trick to allow us to use import * for spikeinterface.full
-    if extractor_name == "__all__":
-        __all__ = []
-        for imp in globals():
-            # need to remove a bunch of builtins etc that shouldn't be part of all
-            if imp[0] != "_" and imp != "warn" and imp != "extractor_name":
-                __all__.append(imp)
-        return __all__
-    all_extractors = list(recording_extractor_full_dict.values())
-    all_extractors += list(sorting_extractor_full_dict.values())
-    all_extractors += list(event_extractor_full_dict.values())
-    all_extractors += list(snippets_extractor_full_dict.values())
-    # special cases because they don't have simple wrappers
-    # instead a single wrapper maps to multiple classes so we return
-    # each class to check it
-    from .neoextractors import (
-        MEArecRecordingExtractor,
-        MEArecSortingExtractor,
-        OpenEphysBinaryEventExtractor,
-        OpenEphysBinaryRecordingExtractor,
-        OpenEphysLegacyRecordingExtractor,
-        SpikeGLXEventExtractor,
-    )
-
-    all_extractors += [
-        MEArecRecordingExtractor,
-        MEArecSortingExtractor,
-        OpenEphysBinaryEventExtractor,
-        OpenEphysBinaryRecordingExtractor,
-        OpenEphysLegacyRecordingExtractor,
-        SpikeGLXEventExtractor,
-    ]
-    for reading_function in all_extractors:
-        if extractor_name == reading_function.__name__:
-            dep_msg = (
-                "Importing classes at __init__ has been deprecated in favor of only importing function-size wrappers "
-                "and will be removed in 0.105.0. For developers that prefer working with the class versions of extractors "
-                "they can be imported from spikeinterface.extractors.extractor_classes"
-                f"For class {reading_function.__name__}"
-            )
-            warn(dep_msg)
-            return reading_function
-    # this is necessary for objects that we don't support
-    # normally this is an ImportError but since this is in the __getattr__ pytest needs an AttributeError
-    raise AttributeError(f"cannot import name '{extractor_name}' from '{__name__}'")
diff --git a/src/spikeinterface/extractors/extractor_classes.py b/src/spikeinterface/extractors/extractor_classes.py
index 1e9f5f6784..a2b11726a8 100644
--- a/src/spikeinterface/extractors/extractor_classes.py
+++ b/src/spikeinterface/extractors/extractor_classes.py
@@ -6,15 +6,17 @@
     NpzSortingExtractor,
     NumpySorting,
     NpySnippetsExtractor,
-    ZarrRecordingExtractor,
-    ZarrSortingExtractor,
     read_binary,
     read_zarr,
     read_npz_sorting,
     read_npy_snippets,
 )
 
-from spikeinterface.core.zarrextractors import read_zarr_array
+from spikeinterface.core.zarrextractors import (
+    ZarrRecordingExtractor,
+    ZarrSortingExtractor,
+    read_zarr_array,
+)
 
 # sorting/recording/event from neo
 from .neoextractors import *
diff --git a/src/spikeinterface/extractors/neoextractors/openephys.py b/src/spikeinterface/extractors/neoextractors/openephys.py
index 824f8d9560..b03f731909 100644
--- a/src/spikeinterface/extractors/neoextractors/openephys.py
+++ b/src/spikeinterface/extractors/neoextractors/openephys.py
@@ -137,10 +137,6 @@ class OpenEphysBinaryRecordingExtractor(NeoBaseRecordingExtractor):
         If True, the synchronized_timestamps are loaded and set as times to the recording.
         If False (default), only the t_start and sampling rate are set, and timestamps are assumed
         to be uniform and linearly increasing
-    experiment_names : str, list, or None, default: None
-        **DEPRECATED: Use experiment_name instead. Will be removed in version 0.105.0**
-        This parameter was designed for Neo's multi-block loading, but SpikeInterface only loads
-        one block at a time. Use experiment_name to select a single experiment.
     all_annotations : bool, default: False
         Load exhaustively all annotation from neo
 
@@ -224,20 +220,10 @@ def __init__(
         stream_name: str = None,
         block_index: int = None,
         load_sync_timestamps: bool = False,
-        experiment_names: str | list | None = None,
         all_annotations: bool = False,
     ):
         folder_path = Path(folder_path)
 
-        # Handle experiment_names deprecation
-        if experiment_names is not None:
-            warnings.warn(
-                "OpenEphysBinaryRecordingExtractor: 'experiment_names' is deprecated and will be removed in version 0.105.0. "
-                "Use 'experiment_name' instead to select a single experiment (e.g., experiment_name='experiment2').",
-                FutureWarning,
-                stacklevel=2,
-            )
-
         # Handle experiment_name and block_index parameters
         if experiment_name is not None and block_index is not None:
             raise ValueError(
@@ -248,7 +234,7 @@ def __init__(
         # Convert experiment_name to experiment_names for Neo
         # When using experiment_name, Neo will filter to only that experiment, making it block_index=0
         # experiment_name takes precedence over experiment_names
-        experiment_names_for_neo = experiment_names  # Use deprecated parameter if provided
+        experiment_names_for_neo = None  # No longer using the deprecated parameter
         if experiment_name is not None:
             # experiment_name overrides experiment_names
             experiment_names_for_neo = [experiment_name]
diff --git a/src/spikeinterface/extractors/tests/test_zarr_array_extractor.py b/src/spikeinterface/extractors/tests/test_zarr_array_extractor.py
index ddab87d4e1..2633a2e41d 100644
--- a/src/spikeinterface/extractors/tests/test_zarr_array_extractor.py
+++ b/src/spikeinterface/extractors/tests/test_zarr_array_extractor.py
@@ -53,7 +53,7 @@ def test_zarr_array_extractor(make_dummy_zarr_data):
     assert np.all(rec.get_channel_offsets() == offset)
 
     # 3. Verify exact trace reading
-    traces_raw = rec.get_traces(return_scaled=False)
+    traces_raw = rec.get_traces(return_in_uV=False)
     np.testing.assert_array_equal(traces_raw, original_data)
 
     # 4. Verify channel and time slicing
diff --git a/src/spikeinterface/metrics/quality/__init__.py b/src/spikeinterface/metrics/quality/__init__.py
index f91ed6eefc..db71887465 100644
--- a/src/spikeinterface/metrics/quality/__init__.py
+++ b/src/spikeinterface/metrics/quality/__init__.py
@@ -2,7 +2,6 @@
     get_quality_metric_list,
     get_quality_pca_metric_list,
     get_default_quality_metrics_params,
-    get_default_qm_params,
     ComputeQualityMetrics,
     compute_quality_metrics,
 )
diff --git a/src/spikeinterface/metrics/quality/quality_metrics.py b/src/spikeinterface/metrics/quality/quality_metrics.py
index c23f6decb7..0e50a4eb79 100644
--- a/src/spikeinterface/metrics/quality/quality_metrics.py
+++ b/src/spikeinterface/metrics/quality/quality_metrics.py
@@ -248,13 +248,3 @@ def get_default_quality_metrics_params(metric_names=None):
         metric_names = list(set(metric_names) & set(default_params.keys()))
         metric_params = {m: default_params[m] for m in metric_names}
         return metric_params
-
-
-def get_default_qm_params(metric_names=None):
-    warnings.warn(
-        "`get_default_qm_params` is deprecated and will be removed in a version 0.105.0. "
-        "Please use `get_default_quality_metrics_params` instead.",
-        FutureWarning,
-        stacklevel=2,
-    )
-    return get_default_quality_metrics_params(metric_names=metric_names)
diff --git a/src/spikeinterface/metrics/template/__init__.py b/src/spikeinterface/metrics/template/__init__.py
index f4520c416f..ea308f5aac 100644
--- a/src/spikeinterface/metrics/template/__init__.py
+++ b/src/spikeinterface/metrics/template/__init__.py
@@ -2,10 +2,8 @@
     ComputeTemplateMetrics,
     compute_template_metrics,
     get_template_metric_list,
-    get_template_metric_names,
     get_single_channel_template_metric_names,
     get_multi_channel_template_metric_names,
     get_default_template_metrics_params,
-    get_default_tm_params,
 )
 from .metrics import get_trough_and_peak_idx
diff --git a/src/spikeinterface/metrics/template/template_metrics.py b/src/spikeinterface/metrics/template/template_metrics.py
index 1a34efe27f..a23343d0ec 100644
--- a/src/spikeinterface/metrics/template/template_metrics.py
+++ b/src/spikeinterface/metrics/template/template_metrics.py
@@ -27,18 +27,6 @@ def get_template_metric_list():
     return get_single_channel_template_metric_names() + get_multi_channel_template_metric_names()
 
 
-def get_template_metric_names():
-    import warnings
-
-    warnings.warn(
-        "get_template_metric_names is deprecated and will be removed in a version 0.105.0. "
-        "Please use get_template_metric_list instead.",
-        FutureWarning,
-        stacklevel=2,
-    )
-    return get_template_metric_list()
-
-
 class ComputeTemplateMetrics(BaseMetricExtension):
     """
     Compute template metrics including:
@@ -365,23 +353,3 @@ def get_default_template_metrics_params(metric_names=None):
         metric_names = list(set(metric_names) & set(default_params.keys()))
         metric_params = {m: default_params[m] for m in metric_names}
         return metric_params
-
-
-def get_default_tm_params(metric_names=None):
-    """
-    Return default dictionary of template metrics parameters.
-
-    Returns
-    -------
-    metric_params : dict
-        Dictionary with default parameters for template metrics.
-    """
-    import warnings
-
-    warnings.warn(
-        "get_default_tm_params is deprecated and will be removed in a version 0.105.0. "
-        "Please use get_default_template_metrics_params instead.",
-        FutureWarning,
-        stacklevel=2,
-    )
-    return get_default_template_metrics_params(metric_names)
diff --git a/src/spikeinterface/postprocessing/__init__.py b/src/spikeinterface/postprocessing/__init__.py
index ca1aa8b135..2495536d03 100644
--- a/src/spikeinterface/postprocessing/__init__.py
+++ b/src/spikeinterface/postprocessing/__init__.py
@@ -43,11 +43,6 @@
 
 from .noise_level import compute_noise_levels, ComputeNoiseLevels
 
-from .template_metrics import (
-    ComputeTemplateMetrics,
-    compute_template_metrics,
-)
-
 from .valid_unit_periods import (
     ComputeValidUnitPeriods,
     compute_valid_unit_periods,
diff --git a/src/spikeinterface/postprocessing/template_metrics.py b/src/spikeinterface/postprocessing/template_metrics.py
deleted file mode 100644
index e4b8689f0e..0000000000
--- a/src/spikeinterface/postprocessing/template_metrics.py
+++ /dev/null
@@ -1,26 +0,0 @@
-import warnings
-
-
-from spikeinterface.metrics.template import ComputeTemplateMetrics as ComputeTemplateMetricsNew
-from spikeinterface.metrics.template import compute_template_metrics as compute_template_metrics_new
-
-
-class ComputeTemplateMetrics(ComputeTemplateMetricsNew):
-    def __init__(self, *args, **kwargs):
-        warnings.warn(
-            "The module 'spikeinterface.postprocessing.template_metrics' is deprecated and will be removed in 0.105.0."
-            "Please use 'spikeinterface.metrics.template' instead.",
-            FutureWarning,
-            stacklevel=2,
-        )
-        super().__init__(*args, **kwargs)
-
-
-def compute_template_metrics(*args, **kwargs):
-    warnings.warn(
-        "The module 'spikeinterface.postprocessing.template_metrics' is deprecated and will be removed in 0.105.0."
-        "Please use 'spikeinterface.metrics.template' instead.",
-        FutureWarning,
-        stacklevel=2,
-    )
-    return compute_template_metrics_new(*args, **kwargs)
diff --git a/src/spikeinterface/postprocessing/valid_unit_periods.py b/src/spikeinterface/postprocessing/valid_unit_periods.py
index cccec63842..214ebb5efc 100644
--- a/src/spikeinterface/postprocessing/valid_unit_periods.py
+++ b/src/spikeinterface/postprocessing/valid_unit_periods.py
@@ -39,8 +39,8 @@ class ComputeValidUnitPeriods(AnalyzerExtension):
     period_duration_s_absolute : float, default: 10.0
         Duration of individual periods used to define good periods, in seconds. Same across all units.
         Note: the margin size will be the same as the period size.
-            A period size of 10s sets the margin to 10s, which means that periods of 10+2*10=30s are used
-            to estimate the false positive and negative rates of the central 10s.
+        A period size of 10s sets the margin to 10s, which means that periods of 10+2*10=30s are used
+        to estimate the false positive and negative rates of the central 10s.
     period_target_num_spikes : int | None, default: 300
         Alternative to period_size_absolute, different for each unit: mean number of spikes that should be present in each estimation period.
         For neurons firing at 10 Hz, this would correspond to periods of 10s (100 spikes / 10 Hz = 10s).
diff --git a/src/spikeinterface/preprocessing/__init__.py b/src/spikeinterface/preprocessing/__init__.py
index 23a5bb30b1..957b5a97cc 100644
--- a/src/spikeinterface/preprocessing/__init__.py
+++ b/src/spikeinterface/preprocessing/__init__.py
@@ -24,34 +24,3 @@
 
 # for snippets
 from .align_snippets import AlignSnippets
-from warnings import warn
-
-
-# deprecation of class import idea from neuroconv
-# this __getattr__ is only triggered if the normal lookup fails so import
-# any of our functions is fine but if someone tries to import a class this raises
-# the warning and then returns the "function" version which will look the same
-# to the end-user
-# to be removed after version 0.105.0
-def __getattr__(preprocessor_name):
-    # we need this trick to allow us to use import * for spikeinterface.full
-    if preprocessor_name == "__all__":
-        __all__ = []
-        for imp in globals():
-            # need to remove a bunch of builtins etc that shouldn't be part of all
-            if imp[0] != "_" and imp != "warn" and imp != "preprocessor_name":
-                __all__.append(imp)
-        return __all__
-    from .preprocessing_classes import _all_preprocesser_dict
-
-    for pp_class, pp_function in _all_preprocesser_dict.items():
-        if preprocessor_name == pp_class.__name__:
-            dep_msg = (
-                "Importing classes at __init__ has been deprecated in favor of only importing functions "
-                "and will be removed in 0.105.0. For developers that prefer working with the class versions of preprocessors "
-                "they can be imported from spikeinterface.preprocessors.preprocessor_classes."
-            )
-            warn(dep_msg)
-            return pp_function
-    # this is necessary for objects that we don't support
-    raise AttributeError(f"cannot import name '{preprocessor_name}' from '{__name__}'")
diff --git a/src/spikeinterface/preprocessing/decimate.py b/src/spikeinterface/preprocessing/decimate.py
index 9462922806..294a3e00f3 100644
--- a/src/spikeinterface/preprocessing/decimate.py
+++ b/src/spikeinterface/preprocessing/decimate.py
@@ -52,8 +52,9 @@ class DecimateRecording(BasePreprocessor):
     -------
     decimate_recording: DecimateRecording
         The decimated recording extractor object. With `antialias=False` the full traces of the
-        child recording segment correspond to the traces of the parent segment as follows:
-            ```<decimated_traces> = <parent_traces>[<decimation_offset>::<decimation_factor>]```
+        child recording segment correspond to the traces of the parent segment as follows::
+
+            <decimated_traces> = <parent_traces>[<decimation_offset>::<decimation_factor>]
 
     """
 
diff --git a/src/spikeinterface/qualitymetrics/__init__.py b/src/spikeinterface/qualitymetrics/__init__.py
deleted file mode 100644
index a6aad78640..0000000000
--- a/src/spikeinterface/qualitymetrics/__init__.py
+++ /dev/null
@@ -1,10 +0,0 @@
-import warnings
-
-warnings.warn(
-    "The module 'spikeinterface.qualitymetrics' is deprecated and will be removed in 0.105.0."
-    "Please use 'spikeinterface.metrics.quality' instead.",
-    FutureWarning,
-    stacklevel=2,
-)
-
-from spikeinterface.metrics.quality import *  # noqa: F403
diff --git a/src/spikeinterface/sortingcomponents/matching/main.py b/src/spikeinterface/sortingcomponents/matching/main.py
index 3da7785c5e..0b054c0638 100644
--- a/src/spikeinterface/sortingcomponents/matching/main.py
+++ b/src/spikeinterface/sortingcomponents/matching/main.py
@@ -17,7 +17,6 @@ def find_spikes_from_templates(
     pipeline_kwargs=None,
     verbose=False,
     job_kwargs=None,
-    **old_kwargs,
 ) -> np.ndarray | tuple[np.ndarray, dict]:
     """Find spike from a recording from given templates.
 
@@ -50,15 +49,8 @@ def find_spikes_from_templates(
     outputs:
         Optionaly returns for debug purpose.
     """
-
-    if len(old_kwargs) > 0:
-        # This is the old behavior and will be remove in 0.105.0
-        warnings.warn(
-            "The signature of find_spikes_from_templates() has changed, now job_kwargs are in separated dict and not flatten"
-            "This warning will raise an error in version 0.105.0"
-        )
-        assert job_kwargs is None
-        job_kwargs = old_kwargs
+    if job_kwargs is None:
+        job_kwargs = {}
 
     if "method" in method_kwargs:
         # for flexibility the caller can put method inside method_kwargs
diff --git a/src/spikeinterface/sortingcomponents/peak_detection/main.py b/src/spikeinterface/sortingcomponents/peak_detection/main.py
index 489be8abea..4332acac0f 100644
--- a/src/spikeinterface/sortingcomponents/peak_detection/main.py
+++ b/src/spikeinterface/sortingcomponents/peak_detection/main.py
@@ -18,7 +18,6 @@ def detect_peaks(
     pipeline_kwargs=None,
     verbose=False,
     job_kwargs=None,
-    **old_kwargs,
 ):
     """Peak detection based on threshold crossing in term of k x MAD.
 
@@ -54,22 +53,13 @@ def detect_peaks(
     This peak detection ported from tridesclous into spikeinterface.
 
     """
-
-    if len(old_kwargs) > 0:
-        # This is the old behavior and will be remove in 0.105.0
-        warnings.warn(
-            "The signature of detect_peaks() has changed, now method_kwargs and job_kwargs are dinstinct params."
-            "This warning will raise an error in version 0.105.0"
-        )
-        assert job_kwargs is None
-        assert method_kwargs is None
-        method_kwargs, job_kwargs = split_job_kwargs(old_kwargs)
+    if method_kwargs is None:
+        method_kwargs = dict()
     else:
-        if method_kwargs is None:
-            method_kwargs = dict()
-        else:
-            # sevral pop later
-            method_kwargs = method_kwargs.copy()
+        # sevral pop later
+        method_kwargs = method_kwargs.copy()
+    if job_kwargs is None:
+        job_kwargs = dict()
 
     if "method" in method_kwargs:
         # for flexibility the caller can put method inside method_kwargs
diff --git a/src/spikeinterface/sortingcomponents/peak_localization/main.py b/src/spikeinterface/sortingcomponents/peak_localization/main.py
index f49298e407..c788f8b7fa 100644
--- a/src/spikeinterface/sortingcomponents/peak_localization/main.py
+++ b/src/spikeinterface/sortingcomponents/peak_localization/main.py
@@ -74,7 +74,6 @@ def localize_peaks(
     verbose=False,
     job_kwargs=None,
     seed=None,
-    **old_kwargs,
 ) -> np.ndarray:
     """Localize peak (spike) in 2D or 3D depending the method.
 
@@ -116,18 +115,10 @@ def localize_peaks(
         Array with estimated location for each spike.
         The dtype depends on the method. ("x", "y") or ("x", "y", "z", "alpha").
     """
-    if len(old_kwargs) > 0:
-        # This is the old behavior and will be remove in 0.105.0
-        warnings.warn(
-            "The signature of localize_peaks() has changed, now method_kwargs and job_kwargs are dinstinct params."
-            "This warning will raise an error in version 0.105.0"
-        )
-        assert job_kwargs is None
-        assert method_kwargs is None
-        method_kwargs, job_kwargs = split_job_kwargs(old_kwargs)
-    else:
-        if method_kwargs is None:
-            method_kwargs = dict()
+    if method_kwargs is None:
+        method_kwargs = dict()
+    if job_kwargs is None:
+        job_kwargs = dict()
 
     if "method" in method_kwargs:
         # for flexibility the caller can put method inside method_kwargs
diff --git a/src/spikeinterface/sortingcomponents/tests/test_peak_selection.py b/src/spikeinterface/sortingcomponents/tests/test_peak_selection.py
index bb0da231d9..e9d8f1987b 100644
--- a/src/spikeinterface/sortingcomponents/tests/test_peak_selection.py
+++ b/src/spikeinterface/sortingcomponents/tests/test_peak_selection.py
@@ -32,7 +32,14 @@ def test_select_peaks():
     )
 
     peak_locations = localize_peaks(
-        recording, peaks, method="center_of_mass", n_jobs=2, chunk_size=10000, progress_bar=True
+        recording,
+        peaks,
+        method="center_of_mass",
+        job_kwargs=dict(
+            n_jobs=2,
+            chunk_size=10000,
+            progress_bar=True,
+        ),
     )
 
     n_peaks = 100
diff --git a/src/spikeinterface/widgets/isi_distribution.py b/src/spikeinterface/widgets/isi_distribution.py
index 54511b4c2a..65bda2341e 100644
--- a/src/spikeinterface/widgets/isi_distribution.py
+++ b/src/spikeinterface/widgets/isi_distribution.py
@@ -31,16 +31,8 @@ def __init__(
         window_ms: float = 100.0,
         bin_ms: float = 1.0,
         backend: str | None = None,
-        sorting: BaseSorting | None = None,
         **backend_kwargs,
     ):
-
-        if sorting is not None:
-            # When removed, make `sorting_analyzer_or_sorting` a required argument rather than None.
-            deprecation_msg = "`sorting` argument is deprecated and will be removed in version 0.105.0. Please use `sorting_analyzer_or_sorting` instead"
-            warn(deprecation_msg, category=FutureWarning, stacklevel=2)
-            sorting_analyzer_or_sorting = sorting
-
         sorting = self.ensure_sorting(sorting_analyzer_or_sorting)
 
         if unit_ids is None:
diff --git a/src/spikeinterface/widgets/potential_merges.py b/src/spikeinterface/widgets/potential_merges.py
index 3a96c1ea56..370efa57eb 100644
--- a/src/spikeinterface/widgets/potential_merges.py
+++ b/src/spikeinterface/widgets/potential_merges.py
@@ -21,7 +21,7 @@ class PotentialMergesWidget(BaseWidget):
     sorting_analyzer : SortingAnalyzer
         The input sorting analyzer
     potential_merges : list of lists or tuples
-        List of potential merges (see `spikeinterface.curation.get_potential_auto_merges`)
+        List of potential merges (see `spikeinterface.curation.compute_merge_unit_groups`)
     segment_index : int
         The segment index to display
     max_spike_samples : int or None, default: None
diff --git a/src/spikeinterface/widgets/rasters.py b/src/spikeinterface/widgets/rasters.py
index 2ec8f42777..91000be7c1 100644
--- a/src/spikeinterface/widgets/rasters.py
+++ b/src/spikeinterface/widgets/rasters.py
@@ -414,21 +414,9 @@ def __init__(
         time_range: list | None = None,
         color="k",
         backend: str | None = None,
-        sorting: BaseSorting | None = None,
-        sorting_analyzer: SortingAnalyzer | None = None,
         sort_by_depth: bool = False,
         **backend_kwargs,
     ):
-        if sorting is not None:
-            # When removed, make `sorting_analyzer_or_sorting` a required argument rather than None.
-            deprecation_msg = "`sorting` argument is deprecated and will be removed in version 0.105.0. Please use `sorting_analyzer_or_sorting` instead"
-            warn(deprecation_msg, category=FutureWarning, stacklevel=2)
-            sorting_analyzer_or_sorting = sorting
-        if sorting_analyzer is not None:
-            deprecation_msg = "`sorting_analyzer` argument is deprecated and will be removed in version 0.105.0. Please use `sorting_analyzer_or_sorting` instead"
-            warn(deprecation_msg, category=FutureWarning, stacklevel=2)
-            sorting_analyzer_or_sorting = sorting_analyzer
-
         sorting = self.ensure_sorting(sorting_analyzer_or_sorting)
 
         segment_indices = validate_segment_indices(segment_indices, sorting)
diff --git a/src/spikeinterface/widgets/spikes_on_traces.py b/src/spikeinterface/widgets/spikes_on_traces.py
index 3079868a54..b28fe25e9d 100644
--- a/src/spikeinterface/widgets/spikes_on_traces.py
+++ b/src/spikeinterface/widgets/spikes_on_traces.py
@@ -37,8 +37,6 @@ class SpikesOnTracesWidget(BaseWidget):
         * "line": classical for low channel count
         * "map": for high channel count use color heat map
         * "auto": auto switch depending on the channel count ("line" if less than 64 channels, "map" otherwise)
-    return_scaled : bool | None, default: None
-            DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: False
         If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
         traces are scaled to uV
@@ -74,7 +72,6 @@ def __init__(
         unit_colors=None,
         sparsity=None,
         mode="auto",
-        return_scaled=None,
         return_in_uV=False,
         cmap="RdBu",
         show_channel_ids=False,
@@ -90,16 +87,6 @@ def __init__(
         backend=None,
         **backend_kwargs,
     ):
-
-        # Handle deprecated return_scaled parameter
-        if return_scaled is not None:
-            warnings.warn(
-                "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-                category=FurtureWarning,
-                stacklevel=2,
-            )
-            return_in_uV = return_scaled
-
         sorting_analyzer = self.ensure_sorting_analyzer(sorting_analyzer)
         self.check_extensions(sorting_analyzer, "unit_locations")
 
diff --git a/src/spikeinterface/widgets/traces.py b/src/spikeinterface/widgets/traces.py
index c9795f3811..62f221b6ca 100644
--- a/src/spikeinterface/widgets/traces.py
+++ b/src/spikeinterface/widgets/traces.py
@@ -29,8 +29,6 @@ class TracesWidget(BaseWidget):
         * "line": classical for low channel count
         * "map": for high channel count use color heat map
         * "auto": auto switch depending on the channel count ("line" if less than 64 channels, "map" otherwise)
-    return_scaled : bool | None, default: None
-            DEPRECATED. Use return_in_uV instead.
     return_in_uV : bool, default: False
         If True and the recording has scaling (gain_to_uV and offset_to_uV properties),
         traces are scaled to uV
@@ -73,7 +71,6 @@ def __init__(
         order_channel_by_depth=False,
         time_range=None,
         mode="auto",
-        return_scaled=None,
         return_in_uV=False,
         cmap="RdBu_r",
         show_channel_ids=False,
@@ -92,16 +89,6 @@ def __init__(
         backend=None,
         **backend_kwargs,
     ):
-
-        # Handle deprecated return_scaled parameter
-        if return_scaled is not None:
-            warnings.warn(
-                "`return_scaled` is deprecated and will be removed in version 0.105.0. Use `return_in_uV` instead.",
-                category=FutureWarning,
-                stacklevel=2,
-            )
-            return_in_uV = return_scaled
-
         if isinstance(recording, BaseRecording):
             recordings = {"rec": recording}
             rec0 = recording
diff --git a/src/spikeinterface/widgets/unit_presence.py b/src/spikeinterface/widgets/unit_presence.py
index f60e0745e7..72a9603544 100644
--- a/src/spikeinterface/widgets/unit_presence.py
+++ b/src/spikeinterface/widgets/unit_presence.py
@@ -33,16 +33,8 @@ def __init__(
         bin_duration_s: float = 0.05,
         smooth_sigma: float = 4.5,
         backend: str | None = None,
-        sorting: BaseSorting | None = None,
         **backend_kwargs,
     ):
-
-        if sorting is not None:
-            # When removed, make `sorting_analyzer_or_sorting` a required argument rather than None.
-            deprecation_msg = "`sorting` argument is deprecated and will be removed in version 0.105.0. Please use `sorting_analyzer_or_sorting` instead"
-            warn(deprecation_msg, category=FutureWarning, stacklevel=2)
-            sorting_analyzer_or_sorting = sorting
-
         sorting = self.ensure_sorting(sorting_analyzer_or_sorting)
 
         if segment_index is None:
diff --git a/src/spikeinterface/widgets/utils_figpack.py b/src/spikeinterface/widgets/utils_figpack.py
index 9d150980a5..46a94f8126 100644
--- a/src/spikeinterface/widgets/utils_figpack.py
+++ b/src/spikeinterface/widgets/utils_figpack.py
@@ -26,7 +26,7 @@ def import_figpack_or_sortingview(use_sortingview: bool):
 
         vv_base = vv_views
         warn(
-            "The 'sortingview' backend is deprecated and will be removed in version 0.105.0. "
+            "The 'sortingview' backend is deprecated and will be removed in version 0.106.0. "
             "Use the 'figpack' backend instead.",
         )
     else: