{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005726892,0.00009382172,0.0001866425,0.0002049815,0.00006088875,0.00008420337,0.00006096802,0.00009596036,0.00001704549],"category_scores_gemma":[0.0006539994,0.00007775837,0.0000211963,0.000470605,0.0002572285,0.0002002939,0.00004576413,0.0002882578,0.000001318026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002496714,"about_ca_system_score_gemma":0.00007718498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004039832,"about_ca_topic_score_gemma":0.0001547283,"domain_scores_codex":[0.9989493,0.0000362203,0.0002190839,0.0003970772,0.0002164381,0.0001819027],"domain_scores_gemma":[0.9980845,0.00159184,0.00005097594,0.0001322911,0.00005551212,0.00008488953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002850981,0.00003478245,0.4795201,0.000006940647,0.000001351158,0.00004554408,0.0008504023,0.0002739649,0.006182326,0.00002912148,1.82078e-7,0.5130268],"study_design_scores_gemma":[0.0007346649,0.000021222,0.8375451,0.00006853109,0.000002901364,0.00001990461,0.000003515534,0.1590396,0.00168793,0.0007572542,0.00003602906,0.00008332758],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9460645,0.00005059308,0.05271022,0.0008032417,0.000212149,0.0001169467,8.495715e-7,0.00002159826,0.00001989943],"genre_scores_gemma":[0.9901164,0.00001233106,0.009362193,0.0003569841,0.0001374886,0.000002659177,0.000007078498,0.000004598122,2.70697e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5129434,"threshold_uncertainty_score":0.3170894,"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."}}