{"id":"W1554051257","doi":"10.1007/978-3-642-15711-0_37","title":"Surgical Task and Skill Classification from Eye Tracking and Tool Motion in Minimally Invasive Surgery","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"National Cancer Institute; Johns Hopkins University; National Institutes of Health; National Science Foundation","keywords":"Task (project management); Gaze; Surgical simulation; Context (archaeology); Invasive surgery; Eye tracking; Motion (physics); Computer science; Artificial intelligence; Medical physics; Computer vision; Surgery; Medicine; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006905777,0.0002972877,0.0003581209,0.001083219,0.0001491513,0.0004091778,0.0002148509,0.0005996295,0.001317873],"category_scores_gemma":[0.005004927,0.0001296562,0.0003200418,0.0005399359,0.0001230975,0.0004304233,0.0003056915,0.000295559,0.000462314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002142719,"about_ca_system_score_gemma":0.0002958688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00703586,"about_ca_topic_score_gemma":0.008989357,"domain_scores_codex":[0.9997789,0.00005550863,0.00002034609,0.00004841627,0.0000504378,0.00004638101],"domain_scores_gemma":[0.9978327,0.001354524,0.0002024166,0.00008608206,0.0004004835,0.0001237484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004845671,0.0006441827,0.4966155,0.0002570488,0.0002746273,0.000233918,0.0004122899,0.01177329,0.1002669,0.0002054473,0.003408292,0.3810629],"study_design_scores_gemma":[0.00003870702,0.000276718,0.9209849,0.0000216597,0.00008083137,0.0002336601,0.0001372698,0.0721353,0.005515413,0.0002500788,0.000299878,0.00002562648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909638,0.000336008,0.006346115,0.00005342973,0.00004563493,0.00003860681,0.0006540937,0.00009830147,0.00146398],"genre_scores_gemma":[0.9964122,0.0001351193,0.002033227,0.00002542131,0.00001869894,0.00001975453,0.0005386876,0.00001633073,0.0008006479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00703586,"threshold_uncertainty_score":0.01398981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02651912413077506,"score_gpt":0.2926344967977726,"score_spread":0.2661153726669976,"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."}}