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"model_id": "2026_W42_unit",
"task": "unit-encoding",
"model_class": "UnitAutoencoder",
"vintage": "2026_W42",
"training": {
"random_seed": 0,
"training_size": 572,
"training_units": 56497,
"validation_size": 75,
"validation_units": 7671,
"testing_size": 149,
"testing_units": 15880
},
"environment": {
"python": "3.11.9",
"xgboost": "3.2.0",
"scikit_learn": "1.8.0",
"numpy": "2.3.5",
"pandas": "3.0.5",
"torch": "2.7.1+cu118",
"ephysatlas": "0.9.0",
"iblatlas": "1.2.0"
},
"method": "hierarchical_gmm",
"granularity": "unit",
"artifacts": {
"autoencoder": "autoencoder.pt",
"config": "config.json",
"scaler": "shared_latent_scaler.joblib",
"types": "types_gmm.joblib",
"subtypes": "subtypes_gmm.joblib",
"subtype_parent": "subtype_parent.npy",
"context_transform": "context_transform.joblib",
"type_weights": "context_weights_types.pt",
"subtype_weights": "context_weights_subtypes.pt",
"members": "members.npz",
"stats": "preprocessing/unit_stats.npz",
"split": "split.json",
"context": [
"agea_vol_pca.npy",
"merfish_vol_pca.npy"
],
"results": [
"results/summary.json"
]
},
"inputs": {
"index": [
"pid",
"cluster"
],
"columns": [
"x",
"y",
"z"
],
"modalities": [
"waveform",
"acg",
"stpc"
]
},
"outputs": {
"kind": "continuous",
"columns": [
"depolarisation_slope",
"recovery_slope",
"repolarisation_slope",
"spatial_spread_um",
"tip_val",
"spike_width_secs",
"predepolarisation_width_secs",
"spike_amplitude",
"peak_to_trough_ratio_log",
"polarity"
],
"feature_order_sha256": "8536d8c5c99959110df046905224cf91de680434287153131d3ba85eaed968af",
"latent_dim": 60
},
"config": {
"architecture": {
"modalities": [
"waveform",
"acg",
"stpc"
],
"modality_latent_dim": 20,
"latent_dim": 60,
"density": "hierarchical Gaussian mixture, full covariances, top-down assignment",
"n_types": 30,
"n_subtypes": 300,
"max_subtypes_per_type": 10,
"min_units_per_subtype": 20
},
"context": {
"n_cell_pcs": 50,
"n_gene_pcs": 50,
"conditions": "the sub-type weights gamma_k(x) gamma_j|k(x) only; the type and sub-type means and covariances are global",
"source_model": "int-brain-lab/ea-encoder-channel",
"data_vintage": "2026_W41"
},
"readout": {
"method": "members",
"description": "each sub-type is represented by its training units, from anywhere in the brain, weighted by their top-down posterior of the sub-type"
},
"preprocessing": {
"waveforms": "per-unit max-abs normalized, 20 channels centred on the peak channel",
"stats_file": "preprocessing/unit_stats.npz",
"mirror_x_to_single_hemisphere": true,
"mirror_x_sign": -1.0
}
},
"data_source": {
"backend": "s3-ibl",
"project": "ibl_neuropixel_brainwide_01_2026_W41",
"requires_one": true
}
}
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