{"id":"W4408776808","doi":"10.1016/j.labinv.2024.103175","title":"941 OCEAN Challenge: Advancing AI for Generalized Ovarian Cancer Diagnosis","year":2025,"lang":"en","type":"article","venue":"Laboratory Investigation","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; Vancouver General Hospital; Canadian Centre for Applied Research in Cancer Control; BC Cancer Agency; BC Cancer Foundation; University of British Columbia","funders":"","keywords":"Ovarian cancer; Cancer; Medicine; Computational biology; Internal medicine; Biology","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":[0.006616333,0.001113108,0.001562291,0.002419704,0.0009178192,0.004633728,0.00216687,0.002692359,0.00959935],"category_scores_gemma":[0.02400566,0.0003961032,0.001079614,0.00125835,0.002048051,0.00388147,0.003854818,0.005729263,0.004460431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001176634,"about_ca_system_score_gemma":0.003512316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00650431,"about_ca_topic_score_gemma":0.009453876,"domain_scores_codex":[0.9975129,0.00105978,0.0001371432,0.0004577721,0.0006649511,0.0001674302],"domain_scores_gemma":[0.9852769,0.009061067,0.0004839136,0.0009999811,0.003220077,0.0009580425],"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":[0.0002898751,0.0001795072,0.01239289,0.0009289058,0.0001976463,0.0003053351,0.0001710277,0.007501916,0.005450124,0.01971628,0.09994178,0.8529248],"study_design_scores_gemma":[0.0002874249,0.0006300598,0.01389392,0.001927307,0.0004800351,0.00271407,0.001446867,0.2710873,0.01156479,0.3075812,0.3881514,0.0002355416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03582776,0.1159334,0.519341,0.269263,0.008065441,0.0003816698,0.004151899,0.005572498,0.04146328],"genre_scores_gemma":[0.3865637,0.06257077,0.4698574,0.04230449,0.01371467,0.0002940666,0.00614288,0.001289843,0.01726225],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00959935,"threshold_uncertainty_score":0.03499097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225138466762397,"score_gpt":0.3204720121160677,"score_spread":0.3082206274484437,"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."}}