{"id":"W4416221296","doi":"10.1097/pas.0000000000002481","title":"Performance Assessment of a Deep Learning–based Algorithm for Ovarian Cancer Histotyping in an Independent Data Set","year":2025,"lang":"en","type":"article","venue":"The American Journal of Surgical Pathology","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ovarian cancer; Voting; Serous fluid; Data set; Domain (mathematical analysis); Domain adaptation; Diagnostic accuracy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.006055369,0.0009339574,0.0007237428,0.0009586036,0.0004809652,0.0008121587,0.001082764,0.001078073,0.0006282539],"category_scores_gemma":[0.00775971,0.0003053425,0.000747542,0.0005425911,0.0004106228,0.0006311457,0.00134095,0.001148508,0.0003654053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009938115,"about_ca_system_score_gemma":0.001195156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007825812,"about_ca_topic_score_gemma":0.007192991,"domain_scores_codex":[0.9986406,0.0005766449,0.0001115416,0.0003206627,0.0002297415,0.0001207433],"domain_scores_gemma":[0.9966126,0.001899647,0.0001910167,0.0004083753,0.0007496306,0.0001387139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002059624,0.0008667484,0.1012846,0.0001335352,0.0007024599,0.0001971956,0.0001978089,0.4386591,0.01006209,0.0007782207,0.003282072,0.4417764],"study_design_scores_gemma":[0.00002707946,0.0001931201,0.004912246,0.000007082158,0.0000221598,0.00003632362,0.00002471885,0.9921443,0.002173895,0.0002441828,0.0002058664,0.000009044605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.932168,0.000686771,0.06360427,0.0004055096,0.0000821688,0.0001850891,0.0004861481,0.001013982,0.001368086],"genre_scores_gemma":[0.9504523,0.000123005,0.0465984,0.0001088784,0.00002196826,0.0001252199,0.001514041,0.00003780727,0.001018497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007825812,"threshold_uncertainty_score":0.03202426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03197782085181015,"score_gpt":0.3495695417127254,"score_spread":0.3175917208609152,"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."}}