{"id":"W4362486902","doi":"10.1117/12.2654234","title":"Cautery tool state detection using deep learning on intraoperative surgery videos","year":2023,"lang":"en","type":"article","venue":"","topic":"Nonmelanoma Skin Cancer Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Margin (machine learning); Artificial intelligence; Deep learning; Computer science; Receiver operating characteristic; Machine learning","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":[0.0002731118,0.000140958,0.000279466,0.0002325169,0.0001906603,0.00002480233,0.00002303408,0.0000420981,0.0001245882],"category_scores_gemma":[0.0002573558,0.0001170449,0.00007459463,0.0004259536,0.00004162621,0.00009519707,0.00004545944,0.0002258972,0.0002363788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002195959,"about_ca_system_score_gemma":0.00005244181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001554084,"about_ca_topic_score_gemma":0.0001444049,"domain_scores_codex":[0.9989519,0.0000662166,0.0002242563,0.0002580799,0.0002172257,0.0002823263],"domain_scores_gemma":[0.9993175,0.0003766705,0.00005214137,0.0001338268,0.0000695828,0.00005026985],"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":[0.001026906,0.0001182206,0.411172,0.0002945301,0.0008247013,0.001172835,0.006120201,0.008687785,0.0472109,0.00005009493,0.00238062,0.5209412],"study_design_scores_gemma":[0.001288419,0.0006817521,0.7485874,0.0004303289,0.0001323744,0.0001651393,0.002543416,0.04035853,0.1979414,0.0001296731,0.007086813,0.0006548293],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947385,0.00005629597,0.002579743,0.0002981075,0.0004412435,0.0002105503,0.000001214415,0.0002603008,0.001414102],"genre_scores_gemma":[0.9968828,0.0001572708,0.0002184567,0.0003150847,0.0002239451,0.00002877133,0.00000602584,0.0000312235,0.00213643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5202863,"threshold_uncertainty_score":0.4772951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0405702645895451,"score_gpt":0.2990861333558216,"score_spread":0.2585158687662765,"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."}}