{"id":"W3211220493","doi":"10.1093/bjs/znab361.022","title":"SP2.1.1Continuous Monitoring and Assessment of Surgical Technical Skills Using Deep Learning","year":2021,"lang":"en","type":"article","venue":"British journal of surgery","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Virtual reality; Forceps; Medical physics; Artificial intelligence; Simulation; Surgery; Computer science","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":[0.00131948,0.001148818,0.0004653993,0.0005272143,0.0002150402,0.0009266355,0.001692857,0.001148081,0.005872922],"category_scores_gemma":[0.002877686,0.0005254738,0.0005415843,0.0003160338,0.0003091844,0.0009065691,0.001292185,0.001091719,0.002229017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004328662,"about_ca_system_score_gemma":0.001304366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002467402,"about_ca_topic_score_gemma":0.002428312,"domain_scores_codex":[0.9994716,0.0001076358,0.00004036728,0.0001641967,0.0001647267,0.00005143748],"domain_scores_gemma":[0.9989857,0.0003542174,0.0000898244,0.0001416939,0.000361234,0.00006742278],"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":[0.001473145,0.001277856,0.02134676,0.0007535684,0.000532286,0.0002988474,0.0002587098,0.2405519,0.0555703,0.004690703,0.0305882,0.6426577],"study_design_scores_gemma":[0.00006673028,0.0004358303,0.002852514,0.00002902378,0.00003941463,0.000113001,0.00001647322,0.9633799,0.02758506,0.001295553,0.004158182,0.00002835296],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1369268,0.000545382,0.7944111,0.0003990839,0.0002155268,0.0007868427,0.002892316,0.05254883,0.0112741],"genre_scores_gemma":[0.5628174,0.00032181,0.4153846,0.0003750124,0.00004891567,0.001302569,0.005609889,0.001512992,0.01262676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005872922,"threshold_uncertainty_score":0.01964694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04037546870545888,"score_gpt":0.3392891681418409,"score_spread":0.298913699436382,"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."}}