diff --git a/examples/toolbox-paper/1_preprocessing.py b/examples/toolbox-paper/1_preprocessing.py
new file mode 100644
index 0000000..81605f5
--- /dev/null
+++ b/examples/toolbox-paper/1_preprocessing.py
@@ -0,0 +1,56 @@
+import os
+from dask.distributed import Client
+
+import osl_ephys
+
+
+if __name__ == "__main__": 
+  client = Client(n_workers=16, threads_per_worker=1) # specify to enable parallel processing
+  basedir = "ds117"
+
+  config = """
+    meta:
+      event_codes:
+        famous/first: 5
+        famous/immediate: 6
+        famous/last: 7
+        unfamiliar/first: 13
+        unfamiliar/immediate: 14
+        unfamiliar/last: 15
+        scrambled/first: 17
+        scrambled/immediate: 18
+        scrambled/last: 19
+    preproc:
+      - find_events: {min_duration: 0.005}
+      - set_channel_types: {EEG061: eog, EEG062: eog, EEG063: ecg}
+      - filter: {l_freq: 0.5, h_freq: 125, method: iir, iir_params: {order: 5, ftype: butter}}
+      - notch_filter: {freqs: 50 100}
+      - resample: {sfreq: 250}
+      - bad_segments: {segment_len: 500, picks: mag}
+      - bad_segments: {segment_len: 500, picks: grad}
+      - bad_segments: {segment_len: 500, picks: mag, mode: diff}
+      - bad_segments: {segment_len: 500, picks: grad, mode: diff}
+      - bad_channels: {picks: mag, significance_level: 0.1}
+      - bad_channels: {picks: grad, significance_level: 0.1}
+      - ica_raw: {picks: meg, n_components: 40}
+      - ica_autoreject: {picks: meg, ecgmethod: correlation, eogmethod: correlation,
+            eogthreshold: 0.35, apply: False}
+      - interpolate_bads: {reset_bads: False}
+      """
+
+  # Study utils enables selection of existing paths using various wild cards
+  study = osl_ephys.utils.Study(os.path.join(basedir, "sub{sub_id}/MEG/run_{run_id}_raw.fif"))
+  inputs = sorted(study.get())
+  
+  # specify session names and output directory
+  subjects = [f"sub{i+1:03d}-run{j+1:02d}" for i in range(19) for j in range(6)]
+  outdir = os.path.join(basedir, "processed")
+
+  osl_ephys.preprocessing.run_proc_batch(
+    config,
+    inputs,
+    subjects,
+    outdir,
+    dask_client=True,
+    random_seed=2280431064,
+  )
diff --git a/examples/toolbox-paper/2_source-reconstruct.py b/examples/toolbox-paper/2_source-reconstruct.py
new file mode 100644
index 0000000..c85d1ef
--- /dev/null
+++ b/examples/toolbox-paper/2_source-reconstruct.py
@@ -0,0 +1,68 @@
+import os
+import numpy as np
+from dask.distributed import Client
+from osl_ephys import source_recon, utils
+
+source_recon.setup_fsl("~/fsl") # FSL needs to be installed
+
+def fix_headshape_points(outdir, subject):
+    filenames = source_recon.rhino.get_coreg_filenames(outdir, subject)
+
+    # Load saved headshape and nasion files
+    hs = np.loadtxt(filenames["polhemus_headshape_file"])
+    nas = np.loadtxt(filenames["polhemus_nasion_file"])
+    lpa = np.loadtxt(filenames["polhemus_lpa_file"])
+    rpa = np.loadtxt(filenames["polhemus_rpa_file"])
+
+    # Remove headshape points on the nose
+    remove = np.logical_and(hs[1] > max(lpa[1], rpa[1]), hs[2] < nas[2])
+    hs = hs[:, ~remove]
+
+    # Overwrite headshape file
+    utils.logger.log_or_print(f"overwritting {filenames['polhemus_headshape_file']}")
+    np.savetxt(filenames["polhemus_headshape_file"], hs)
+
+if __name__ == "__main__":
+    utils.logger.set_up(level="INFO")
+    client = Client(n_workers=16, threads_per_worker=1)
+
+    config = """
+        source_recon:
+        - extract_polhemus_from_info: {}
+        - fix_headshape_points: {}
+        - compute_surfaces:
+            include_nose: False
+        - coregister:
+            use_nose: False
+            use_headshape: True
+        - forward_model:
+            model: Single Layer
+        - beamform_and_parcellate:
+            freq_range: [1, 45]
+            chantypes: [mag, grad]
+            rank: {meg: 60}
+            parcellation_file: Glasser52_binary_space-MNI152NLin6_res-8x8x8.nii.gz
+            method: spatial_basis
+            orthogonalisation: symmetric
+    """
+
+    basedir = "ds117"
+    proc_dir = os.path.join(basedir, "processed")
+
+    # Define inputs
+    subjects = [f"sub{i+1:03d}-run{j+1:02d}" for i in range(19) for j in range(6)]
+    preproc_files = sorted(utils.Study(os.path.join(proc_dir, "sub{sub_id}-    run{run_id}/sub{sub_id}-run{run_id}_preproc-raw.fif")).get())
+    smri_files = np.concatenate([[smri_file]*6 for smri_file in sorted(utils.Study(os.path.join(basedir, "sub{sub_id}/anatomy/highres001.nii.gz"))).get()])
+
+    # Run source batch
+    source_recon.run_src_batch(
+        config,
+        outdir=proc_dir,
+        subjects=subjects,
+        preproc_files=preproc_files,
+        smri_files=smri_files,
+        extra_funcs=[fix_headshape_points],
+        dask_client=True,
+        random_seed=1392754308,
+    )
+
diff --git a/examples/toolbox-paper/3_sign-flip.py b/examples/toolbox-paper/3_sign-flip.py
new file mode 100644
index 0000000..20e75d7
--- /dev/null
+++ b/examples/toolbox-paper/3_sign-flip.py
@@ -0,0 +1,46 @@
+
+import os
+from glob import glob
+from dask.distributed import Client
+
+from osl_ephys import source_recon, utils
+
+source_recon.setup_fsl("~/fsl")
+
+# Directory containing source reconstructed data
+proc_dir = "ds117/processed"
+src_files = sorted(utils.Study(os.path.join(proc_dir, 
+"sub{sub_id}-run{run_id}/parc/parc-raw.fif")).get())
+
+if __name__ == "__main__":
+    utils.logger.set_up(level="INFO")
+
+    subjects = [f"sub{i+1:03d}-run{j+1:02d}" for i in range(19) for j in range(6)]
+         
+    # Find a good template subject to match others to
+    template = source_recon.find_template_subject(
+        proc_dir, subjects, n_embeddings=15, standardize=True,
+    )
+
+    # Settings
+    config = f"""
+        source_recon:
+        - fix_sign_ambiguity:
+            template: {template}
+            n_embeddings: 15
+            standardize: True
+            n_init: 3
+            n_iter: 3000
+            max_flips: 20
+    """
+
+    # Setup parallel processing
+    client = Client(n_workers=16, threads_per_worker=1)
+
+    # Run sign flipping
+    source_recon.run_src_batch(config, proc_dir, subjects, dask_client=True, random_seed=3116145039)
+
+
+
+
+
diff --git a/examples/toolbox-paper/4_stats.py b/examples/toolbox-paper/4_stats.py
new file mode 100644
index 0000000..9af0d95
--- /dev/null
+++ b/examples/toolbox-paper/4_stats.py
@@ -0,0 +1,46 @@
+import os
+import numpy as np
+import glmtools
+import matplotlib.pyplot as plt
+from dask.distributed import Client
+from osl_ephys import preprocessing, glm
+
+    
+if __name__ == "__main__":
+    client = Client(n_workers=16, threads_per_worker=1)
+  
+    config = """
+      preproc:
+        - read_dataset: {ftype: sflip_parc-raw}
+        - epochs: {picks: misc, tmin: -0.2, tmax: 0.3}
+        - glm_add_regressor: {name: famous, rtype: Categorical, codes: [5 6 7]}
+        - glm_add_regressor: {name: unfamiliar, rtype: Categorical, codes: [13 14 15]}
+        - glm_add_regressor: {name: scrambled, rtype: Categorical, codes: [17 18 19]}
+        - glm_add_contrast: {name: Mean, values: {famous: 1/3, unfamiliar: 1/3, scrambled: 1/3}}
+        - glm_add_contrast: {name: Faces-Scrambled, values: {famous: 1, unfamiliar: 1, scrambled: -2}}
+        - glm_fit: {target: epochs, method: glm_epochs}
+      group:
+        - glm_add_regressor: {name: Subject, rtype: Categorical, key: Subject, codes: unique}
+        - glm_add_contrast: {name: Mean, values: unique, key: Subject}
+        - glm_fit: {method: epochs, tmin: 0.05, tmax: 0.3}
+        - glm_permutations: {method: epochs, target: group_glm, contrast: Mean, type: max, nperms: 1000, threshold: 0.99}
+    """    
+    proc_dir = "ds117/processed"
+    src_files = sorted(utils.Study(os.path.join(proc_dir, 
+"sub{sub_id}-run{run_id}", "sub{sub_id}-run{run_id}_sflip_parc-raw.fif")).get())    
+    subjects = [f"sub{i+1:03d}-run{j+1:02d}" for i in range(19) for j in range(6)]
+    covs = [f"Subject": [sub.split("-")[0]for sub in subjects]
+
+    preprocessing.run_proc_batch(
+        config,
+        src_files,
+        subjects,
+        outdir=proc_dir,
+        ftype='raw',
+        covs=covs,
+        dask_client=True,
+        overwrite=True,
+        gen_report=False,
+        skip_save=['events', 'raw', 'ica', 'event_id', 'sflip_parc-raw'],
+    )
+
diff --git a/examples/toolbox-paper/README.md b/examples/toolbox-paper/README.md
new file mode 100644
index 0000000..6ea7133
--- /dev/null
+++ b/examples/toolbox-paper/README.md
@@ -0,0 +1,22 @@
+# OSL Toolbox Paper
+
+The scripts for the toolbox paper can be found here in the order they appear in the manuscript. You can download the data from [OpenfMRI](https://openfmri.org/s3-browser/?prefix=ds000117/ds000117_R0.1.1/compressed/). Extract the `tar.gz` files in a folder called `ds117`. Note: you may have to change the base directory in the scripts to match the directory where you store the data. You also need to [install FSL](https://fsl.fmrib.ox.ac.uk/fsl/docs/#/install/index), and make sure that `source_recon.setup_fsl()` in `2_source-reconstruct.py` and `3_sign-flip.py` is pointing to the correct directory.
+
+If you wish to fully reproduce the analysis pipeline install the environment specified in `osl-toolbox-paper.yml`, and set `random_seed` in `run_proc_batch` and `run_src_batch` according to the seed found in the logfiles on [OSF](https://osf.io/2rnyg/).
+
+## Manual preprocessing
+
+Note that in the toolbox paper, automatically labeled ICA components were manually refined for the following sessions:
+- sub008-ses03
+- sub019-ses01
+- sub019-ses02
+- sub019-ses03
+- sub019-ses04
+- sub019-ses05
+- sub019-ses06
+- sub010-ses05
+
+This was done by running the following command line function iteratively, replacing "session". 
+`osl_ica_label None processed "session"`
+After all specified sessions were refined, all automatically/manually labeled components were removed from the preprocessed MEG data using the command line call
+`osl_ica_apply processed`
\ No newline at end of file
diff --git a/examples/toolbox-paper/osl-toolbox-paper.yml b/examples/toolbox-paper/osl-toolbox-paper.yml
new file mode 100644
index 0000000..51dacff
--- /dev/null
+++ b/examples/toolbox-paper/osl-toolbox-paper.yml
@@ -0,0 +1,366 @@
+name: osl-toolbox-paper
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - _libgcc_mutex=0.1=conda_forge
+  - _openmp_mutex=4.5=2_gnu
+  - aom=3.5.0=h27087fc_0
+  - brotli-python=1.1.0=py38h17151c0_1
+  - bzip2=1.0.8=h4bc722e_7
+  - c-ares=1.32.2=h4bc722e_0
+  - ca-certificates=2024.7.4=hbcca054_0
+  - certifi=2024.7.4=pyhd8ed1ab_0
+  - cffi=1.16.0=py38h6d47a40_0
+  - charset-normalizer=3.3.2=pyhd8ed1ab_0
+  - curl=8.8.0=he654da7_1
+  - double-conversion=3.2.0=h27087fc_1
+  - eigen=3.4.0=h00ab1b0_0
+  - elfutils=0.190=h924a536_1
+  - expat=2.6.2=h59595ed_0
+  - ffmpeg=4.4.2=gpl_h8dda1f0_112
+  - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
+  - font-ttf-inconsolata=3.000=h77eed37_0
+  - font-ttf-source-code-pro=2.038=h77eed37_0
+  - font-ttf-ubuntu=0.83=h77eed37_2
+  - fontconfig=2.14.2=h14ed4e7_0
+  - fonts-conda-ecosystem=1=0
+  - fonts-conda-forge=1=0
+  - freetype=2.12.1=h267a509_2
+  - gettext=0.22.5=h59595ed_2
+  - gettext-tools=0.22.5=h59595ed_2
+  - gl2ps=1.4.2=h0708190_0
+  - gmp=6.3.0=hac33072_2
+  - gnutls=3.7.9=hb077bed_0
+  - h2=4.1.0=py38h578d9bd_0
+  - hdf4=4.2.15=h9772cbc_5
+  - hdf5=1.12.2=nompi_h4df4325_101
+  - hpack=4.0.0=pyh9f0ad1d_0
+  - hyperframe=6.0.1=pyhd8ed1ab_0
+  - icu=73.2=h59595ed_0
+  - idna=3.7=pyhd8ed1ab_0
+  - imageio=2.34.2=pyh12aca89_0
+  - jpeg=9e=h0b41bf4_3
+  - jsoncpp=1.9.5=h4bd325d_1
+  - keyutils=1.6.1=h166bdaf_0
+  - krb5=1.21.3=h659f571_0
+  - lame=3.100=h166bdaf_1003
+  - lcms2=2.14=h6ed2654_0
+  - ld_impl_linux-64=2.40=hf3520f5_7
+  - lerc=4.0.0=h27087fc_0
+  - libaec=1.1.3=h59595ed_0
+  - libarchive=3.7.4=hfca40fe_0
+  - libasprintf=0.22.5=h661eb56_2
+  - libasprintf-devel=0.22.5=h661eb56_2
+  - libblas=3.9.0=22_linux64_openblas
+  - libcblas=3.9.0=22_linux64_openblas
+  - libcurl=8.8.0=hca28451_1
+  - libdeflate=1.14=h166bdaf_0
+  - libdrm=2.4.122=h4ab18f5_0
+  - libedit=3.1.20191231=he28a2e2_2
+  - libev=4.33=hd590300_2
+  - libexpat=2.6.2=h59595ed_0
+  - libffi=3.4.2=h7f98852_5
+  - libgcc-ng=14.1.0=h77fa898_0
+  - libgettextpo=0.22.5=h59595ed_2
+  - libgettextpo-devel=0.22.5=h59595ed_2
+  - libgfortran-ng=14.1.0=h69a702a_0
+  - libgfortran5=14.1.0=hc5f4f2c_0
+  - libgomp=14.1.0=h77fa898_0
+  - libhwloc=2.11.1=default_hecaa2ac_1000
+  - libiconv=1.17=hd590300_2
+  - libidn2=2.3.7=hd590300_0
+  - liblapack=3.9.0=22_linux64_openblas
+  - libllvm16=16.0.6=hb3ce162_3
+  - libmicrohttpd=1.0.1=h97afed2_0
+  - libnetcdf=4.8.1=nompi_h261ec11_106
+  - libnghttp2=1.58.0=h47da74e_1
+  - libnsl=2.0.1=hd590300_0
+  - libogg=1.3.5=h4ab18f5_0
+  - libopenblas=0.3.27=pthreads_hac2b453_1
+  - libpciaccess=0.18=hd590300_0
+  - libpng=1.6.43=h2797004_0
+  - libsqlite=3.46.0=hde9e2c9_0
+  - libssh2=1.11.0=h0841786_0
+  - libstdcxx-ng=14.1.0=hc0a3c3a_0
+  - libtasn1=4.19.0=h166bdaf_0
+  - libtheora=1.1.1=h4ab18f5_1006
+  - libtiff=4.4.0=h82bc61c_5
+  - libunistring=0.9.10=h7f98852_0
+  - libuuid=2.38.1=h0b41bf4_0
+  - libva=2.18.0=h0b41bf4_0
+  - libvorbis=1.3.7=h9c3ff4c_0
+  - libvpx=1.11.0=h9c3ff4c_3
+  - libwebp-base=1.4.0=hd590300_0
+  - libxcb=1.13=h7f98852_1004
+  - libxml2=2.12.7=hc051c1a_1
+  - libzip=1.10.1=h2629f0a_3
+  - libzlib=1.2.13=h4ab18f5_6
+  - loguru=0.7.2=py38h578d9bd_1
+  - lz4-c=1.9.4=hcb278e6_0
+  - lzo=2.10=hd590300_1001
+  - mesalib=23.0.2=h3855f93_0
+  - ncurses=6.5=h59595ed_0
+  - nettle=3.9.1=h7ab15ed_0
+  - openh264=2.3.1=hcb278e6_2
+  - openjpeg=2.5.0=h7d73246_1
+  - openssl=3.3.1=h4bc722e_2
+  - p11-kit=0.24.1=hc5aa10d_0
+  - packaging=24.1=pyhd8ed1ab_0
+  - pillow=9.2.0=py38h9eb91d8_3
+  - pip=23.3.1=pyhd8ed1ab_0
+  - platformdirs=4.2.2=pyhd8ed1ab_0
+  - pooch=1.8.2=pyhd8ed1ab_0
+  - proj=9.0.1=h93bde94_1
+  - pthread-stubs=0.4=h36c2ea0_1001
+  - pugixml=1.11.4=h59595ed_1
+  - pycparser=2.22=pyhd8ed1ab_0
+  - pysocks=1.7.1=pyha2e5f31_6
+  - python=3.8.16=he550d4f_1_cpython
+  - python_abi=3.8=4_cp38
+  - pyvista=0.38.5=pyhd8ed1ab_0
+  - readline=8.2=h8228510_1
+  - requests=2.32.3=pyhd8ed1ab_0
+  - scooby=0.10.0=pyhd8ed1ab_0
+  - setuptools=71.0.4=pyhd8ed1ab_0
+  - sqlite=3.46.0=h6d4b2fc_0
+  - svt-av1=1.4.1=hcb278e6_0
+  - tbb=2021.12.0=h434a139_3
+  - tbb-devel=2021.12.0=hfcbfbdb_3
+  - tk=8.6.13=noxft_h4845f30_101
+  - typing_extensions=4.12.2=pyha770c72_0
+  - urllib3=2.2.2=pyhd8ed1ab_1
+  - utfcpp=4.0.5=ha770c72_0
+  - vtk=9.1.0=osmesa_py38h68dc7f3_115
+  - wheel=0.43.0=pyhd8ed1ab_1
+  - x264=1!164.3095=h166bdaf_2
+  - x265=3.5=h924138e_3
+  - xorg-damageproto=1.2.1=h7f98852_1002
+  - xorg-fixesproto=5.0=h7f98852_1002
+  - xorg-glproto=1.4.17=h7f98852_1002
+  - xorg-kbproto=1.0.7=h7f98852_1002
+  - xorg-libice=1.0.10=h7f98852_0
+  - xorg-libsm=1.2.3=hd9c2040_1000
+  - xorg-libx11=1.8.4=h0b41bf4_0
+  - xorg-libxau=1.0.11=hd590300_0
+  - xorg-libxdamage=1.1.5=h7f98852_1
+  - xorg-libxdmcp=1.1.3=h7f98852_0
+  - xorg-libxext=1.3.4=h0b41bf4_2
+  - xorg-libxfixes=5.0.3=h7f98852_1004
+  - xorg-libxrandr=1.5.2=h7f98852_1
+  - xorg-libxrender=0.9.10=h7f98852_1003
+  - xorg-libxt=1.3.0=hd590300_0
+  - xorg-randrproto=1.5.0=h7f98852_1001
+  - xorg-renderproto=0.11.1=h7f98852_1002
+  - xorg-util-macros=1.19.3=h7f98852_0
+  - xorg-xextproto=7.3.0=h0b41bf4_1003
+  - xorg-xf86vidmodeproto=2.3.1=h7f98852_1002
+  - xorg-xproto=7.0.31=h7f98852_1007
+  - xz=5.2.6=h166bdaf_0
+  - zlib=1.2.13=h4ab18f5_6
+  - zstandard=0.23.0=py38h62bed22_0
+  - zstd=1.5.6=ha6fb4c9_0
+  - pip:
+    - absl-py==2.1.0
+    - alabaster==0.7.13
+    - anamnesis==1.0.4
+    - anyio==4.4.0
+    - argon2-cffi==23.1.0
+    - argon2-cffi-bindings==21.2.0
+    - arrow==1.3.0
+    - asttokens==2.4.1
+    - astunparse==1.6.3
+    - async-lru==2.0.4
+    - attrs==23.2.0
+    - babel==2.15.0
+    - backcall==0.2.0
+    - beautifulsoup4==4.12.3
+    - bleach==6.1.0
+    - bokeh==3.1.1
+    - bounded-pool-executor==0.0.3
+    - cachetools==5.4.0
+    - click==8.1.7
+    - cloudpickle==3.0.0
+    - comm==0.2.2
+    - contourpy==1.1.1
+    - cycler==0.12.1
+    - dask==2023.3.2
+    - debugpy==1.8.2
+    - decorator==5.1.1
+    - defusedxml==0.7.1
+    - dill==0.3.8
+    - distributed==2023.3.2
+    - dm-tree==0.1.8
+    - docutils==0.20.1
+    - exceptiongroup==1.2.2
+    - executing==2.0.1
+    - fastjsonschema==2.20.0
+    - flatbuffers==24.3.25
+    - fonttools==4.53.1
+    - fqdn==1.5.1
+    - fslpy==3.11.3
+    - fsspec==2024.6.1
+    - gast==0.4.0
+    - glmtools==0.2.1
+    - google-auth==2.32.0
+    - google-auth-oauthlib==0.4.6
+    - google-pasta==0.2.0
+    - grpcio==1.65.1
+    - h11==0.14.0
+    - h5io==0.1.7
+    - h5py==3.11.0
+    - httpcore==1.0.5
+    - httpx==0.27.0
+    - imagesize==1.4.1
+    - importlib-metadata==4.13.0
+    - importlib-resources==6.4.0
+    - ipycanvas==0.13.2
+    - ipyevents==2.0.1
+    - ipykernel==6.29.5
+    - ipympl==0.9.3
+    - ipython==8.12.3
+    - ipython-genutils==0.2.0
+    - ipyvtklink==0.2.2
+    - ipywidgets==8.0.5
+    - isoduration==20.11.0
+    - jedi==0.19.1
+    - jinja2==3.0.3
+    - joblib==1.4.2
+    - json5==0.9.25
+    - jsonpointer==3.0.0
+    - jsonschema==4.23.0
+    - jsonschema-specifications==2023.12.1
+    - jupyter==1.0.0
+    - jupyter-client==8.1.0
+    - jupyter-console==6.6.3
+    - jupyter-core==5.7.2
+    - jupyter-events==0.10.0
+    - jupyter-lsp==2.2.5
+    - jupyter-server==2.14.2
+    - jupyter-server-terminals==0.5.3
+    - jupyterlab==4.2.4
+    - jupyterlab-pygments==0.3.0
+    - jupyterlab-server==2.27.3
+    - jupyterlab-widgets==3.0.11
+    - keras==2.11.0
+    - kiwisolver==1.4.5
+    - libclang==18.1.1
+    - linkify-it-py==2.0.3
+    - llvmlite==0.41.1
+    - locket==1.0.0
+    - lxml==5.2.2
+    - markdown==3.6
+    - markdown-it-py==3.0.0
+    - markupsafe==2.1.5
+    - mat73==0.62
+    - matplotlib==3.7.1
+    - matplotlib-inline==0.1.7
+    - mdit-py-plugins==0.4.1
+    - mdurl==0.1.2
+    - mistune==3.0.2
+    - mne==1.3.1
+    - msgpack==1.0.8
+    - nbclient==0.10.0
+    - nbconvert==7.16.4
+    - nbformat==5.10.4
+    - nest-asyncio==1.6.0
+    - neurokit2==0.2.3
+    - nibabel==5.1.0
+    - nilearn==0.10.2
+    - notebook==7.2.1
+    - notebook-shim==0.2.4
+    - numba==0.58.0
+    - numpy==1.23.5
+    - numpydoc==1.7.0
+    - oauthlib==3.2.2
+    - opencv-python==4.7.0.72
+    - opt-einsum==3.3.0
+    - osfclient==0.0.5
+    - overrides==7.7.0
+    - pandas==1.5.3
+    - pandocfilters==1.5.1
+    - panel==1.2.3
+    - param==2.1.1
+    - parse==1.19.0
+    - parso==0.8.4
+    - partd==1.4.1
+    - pexpect==4.9.0
+    - pickleshare==0.7.5
+    - pkgutil-resolve-name==1.3.10
+    - pqdm==0.2.0
+    - prometheus-client==0.20.0
+    - prompt-toolkit==3.0.47
+    - protobuf==3.19.6
+    - psutil==6.0.0
+    - ptyprocess==0.7.0
+    - pure-eval==0.2.3
+    - pyasn1==0.6.0
+    - pyasn1-modules==0.4.0
+    - pygments==2.18.0
+    - pyparsing==3.1.2
+    - python-dateutil==2.9.0.post0
+    - python-json-logger==2.0.7
+    - pytz==2024.1
+    - pyviz-comms==3.0.2
+    - pyyaml==6.0.1
+    - pyzmq==26.0.3
+    - qtconsole==5.5.2
+    - qtpy==2.4.1
+    - referencing==0.35.1
+    - requests-oauthlib==2.0.0
+    - rfc3339-validator==0.1.4
+    - rfc3986-validator==0.1.1
+    - rpds-py==0.19.0
+    - rsa==4.9
+    - sails==1.6.0
+    - scikit-learn==1.3.1
+    - scipy==1.10.1
+    - seaborn==0.13.0
+    - send2trash==1.8.3
+    - six==1.16.0
+    - sniffio==1.3.1
+    - snowballstemmer==2.2.0
+    - sortedcontainers==2.4.0
+    - soupsieve==2.5
+    - sphinx==7.1.2
+    - sphinx-rtd-theme==2.0.0
+    - sphinxcontrib-applehelp==1.0.4
+    - sphinxcontrib-devhelp==1.0.2
+    - sphinxcontrib-htmlhelp==2.0.1
+    - sphinxcontrib-jquery==4.1
+    - sphinxcontrib-jsmath==1.0.1
+    - sphinxcontrib-qthelp==1.0.3
+    - sphinxcontrib-serializinghtml==1.1.5
+    - stack-data==0.6.3
+    - tabulate==0.9.0
+    - tblib==3.0.0
+    - tensorboard==2.11.2
+    - tensorboard-data-server==0.6.1
+    - tensorboard-plugin-wit==1.8.1
+    - tensorflow==2.11.0
+    - tensorflow-estimator==2.11.0
+    - tensorflow-io-gcs-filesystem==0.34.0
+    - tensorflow-probability==0.19.0
+    - termcolor==2.4.0
+    - terminado==0.18.1
+    - threadpoolctl==3.5.0
+    - tinycss2==1.3.0
+    - tomli==2.0.1
+    - toolz==0.12.1
+    - tornado==6.4.1
+    - tqdm==4.66.1
+    - traitlets==5.14.3
+    - types-python-dateutil==2.9.0.20240316
+    - uc-micro-py==1.0.3
+    - uri-template==1.3.0
+    - wcwidth==0.2.13
+    - webcolors==24.6.0
+    - webencodings==0.5.1
+    - websocket-client==1.8.0
+    - werkzeug==3.0.3
+    - widgetsnbextension==4.0.11
+    - wrapt==1.16.0
+    - xyzservices==2024.6.0
+    - zict==3.0.0
+    - zipp==3.19.2
+prefix: osl-toolbox-paper