{"id":"W4283394211","doi":"10.1017/cjn.2022.224","title":"P.140 Development and predictive validation of an intelligent surgical bimanual skills continuous assessment system","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Psychomotor learning; Neurosurgery; Medicine; Task (project management); Physical therapy; Predictive validity; Medical physics; Physical medicine and rehabilitation; Medical education; Psychology; Surgery; Cognition; Psychiatry; Clinical psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001539615,0.0004093105,0.0002177216,0.0006815185,0.0001850676,0.0006415772,0.000550419,0.000413507,0.001825084],"category_scores_gemma":[0.005274983,0.000165609,0.0002684724,0.0003309487,0.0001797075,0.0005329225,0.0005003881,0.0003977644,0.0006644271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004408527,"about_ca_system_score_gemma":0.0006501532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003370155,"about_ca_topic_score_gemma":0.001938687,"domain_scores_codex":[0.9994361,0.0001519237,0.00005680088,0.0001280382,0.0001977393,0.00002932393],"domain_scores_gemma":[0.9979447,0.0008887231,0.000163102,0.0001199575,0.0008239059,0.00005960988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009101688,0.0007858494,0.08619318,0.0001342985,0.0002113186,0.0002367974,0.0002697357,0.06166395,0.03239766,0.001408959,0.005075427,0.8107127],"study_design_scores_gemma":[0.00005865127,0.0006340974,0.03673378,0.00003829454,0.00006700084,0.0002144767,0.0000496619,0.9424264,0.01652508,0.0009005966,0.00231898,0.0000329687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4387838,0.0002189034,0.5457757,0.0003777574,0.000141958,0.0008942332,0.001000243,0.006983067,0.005824308],"genre_scores_gemma":[0.8120837,0.00006991017,0.1845219,0.0001306678,0.0000299878,0.0004541845,0.0009604461,0.00006297213,0.001686241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003370155,"threshold_uncertainty_score":0.008142352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07594068553909249,"score_gpt":0.3656296915163248,"score_spread":0.2896890059772323,"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."}}