{"id":"W4402384993","doi":"10.1177/19160216241278653","title":"Tumor Bed Margins Versus Specimen Margins in Oral Cavity Cancer: Too Close to Call?","year":2024,"lang":"en","type":"article","venue":"Journal of Otolaryngology - Head and Neck Surgery","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; Université Laval","funders":"Centre Hospitalier Universitaire de Québec","keywords":"Medicine; Oral cavity; Sampling (signal processing); Margin (machine learning); Cancer; Surgery; Standard of care; Oral Cancers; Radiology; Dentistry; Internal medicine; Computer science; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002724765,0.0001804702,0.0003137998,0.0004989533,0.0001667052,0.0004543629,0.0002667626,0.0002497047,0.0006546189],"category_scores_gemma":[0.007269244,0.00010174,0.0002604034,0.0004769692,0.0006004085,0.0003560105,0.000452823,0.0002490337,0.0001020812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001875337,"about_ca_system_score_gemma":0.0001663461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003119897,"about_ca_topic_score_gemma":0.0007429729,"domain_scores_codex":[0.9989484,0.0003492216,0.0001051989,0.0001703103,0.0003575045,0.00006940621],"domain_scores_gemma":[0.9930946,0.003517538,0.002509526,0.0003487103,0.0003371708,0.0001925557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007198179,0.00001793097,0.9685573,0.00008068015,0.00004730244,0.0001628716,0.0001629908,0.0001849069,0.002295017,0.00004653449,0.00006651389,0.02765814],"study_design_scores_gemma":[0.00001455664,0.001460312,0.988404,0.0000678787,0.0001304529,0.003480665,0.0004682541,0.0006789062,0.00429978,0.0002458391,0.0007358739,0.0000134912],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964122,0.002472559,0.0007318169,0.00004307202,0.00001513674,0.000007878926,0.00003111069,0.000006111795,0.0002801861],"genre_scores_gemma":[0.9991612,0.0002901875,0.0004305877,0.00001593595,0.00002042002,0.000003322567,0.00002855737,0.000002086496,0.00004759142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002724765,"threshold_uncertainty_score":0.01441014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03626800392620366,"score_gpt":0.3274063126763286,"score_spread":0.291138308750125,"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."}}