{"id":"W4401591794","doi":"10.1038/s41597-024-03683-5","title":"The NACOB multi-surface walking dataset","year":2024,"lang":"en","type":"article","venue":"Scientific Data","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut national de psychiatrie légale Philippe-Pinel; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; McGill University","funders":"Fonds de Recherche du Québec - Santé; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Computer science; Information retrieval; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003391582,0.00128777,0.0008758657,0.001376137,0.0005107367,0.0005063255,0.001422005,0.001301882,0.005339289],"category_scores_gemma":[0.001369837,0.0001912129,0.000884638,0.001252535,0.0002774278,0.0003253124,0.0009686461,0.0006311009,0.005900369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003157224,"about_ca_system_score_gemma":0.0006112453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01211049,"about_ca_topic_score_gemma":0.04215076,"domain_scores_codex":[0.9996464,0.00005374066,0.00004193345,0.00009713281,0.0001090036,0.00005175064],"domain_scores_gemma":[0.9996037,0.00005968216,0.00003208938,0.00009745499,0.0001499535,0.00005729498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001866423,0.001531475,0.06115464,0.002742382,0.0005657834,0.001852729,0.0003752634,0.01468811,0.01018625,0.00157636,0.7095824,0.1938781],"study_design_scores_gemma":[0.0008594246,0.001339431,0.3471451,0.0009567062,0.0002916523,0.003278855,0.001660262,0.09562961,0.009247302,0.00525642,0.5340106,0.0003246389],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1560343,0.001256791,0.01057135,0.0004357912,0.0004476246,0.0006272437,0.8186168,0.004741203,0.007268921],"genre_scores_gemma":[0.07568181,0.0002298062,0.008620412,0.00009064526,0.00003727979,0.000643097,0.9124059,0.0001072785,0.002183761],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01211049,"threshold_uncertainty_score":0.02408004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06017147036614638,"score_gpt":0.2995975986565877,"score_spread":0.2394261282904414,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}