{"id":"W4403251157","doi":"10.1016/j.ygyno.2024.07.394","title":"Machine learning for prediction of concurrent endometrial carcinoma patients diagnosed with endometrial intraepithelial neoplasia","year":2024,"lang":"en","type":"article","venue":"Gynecologic Oncology","topic":"AI in cancer detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Jewish General Hospital","funders":"","keywords":"Medicine; Carcinoma; Oncology; Internal medicine; Gynecology","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":[0.000986981,0.0004229991,0.0005047185,0.001462175,0.0003172719,0.0007591636,0.0005918189,0.0006871635,0.001601259],"category_scores_gemma":[0.005601616,0.0001674063,0.0006428086,0.0005403102,0.0001634647,0.0004616888,0.0003762971,0.0006783925,0.000331158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002599992,"about_ca_system_score_gemma":0.0004108282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003503612,"about_ca_topic_score_gemma":0.003519249,"domain_scores_codex":[0.9996276,0.0001284694,0.00004890881,0.00008204342,0.00004850321,0.00006455802],"domain_scores_gemma":[0.9970441,0.002004965,0.0003585801,0.0001150497,0.0002523453,0.0002248841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009841881,0.000209878,0.9664611,0.00003056194,0.0001573062,0.0001607772,0.0000225341,0.006937745,0.0005610872,0.00009091389,0.0006471829,0.02373665],"study_design_scores_gemma":[0.0000851033,0.0005714489,0.4335075,0.00005417822,0.0003897002,0.0007315714,0.0002414729,0.5608301,0.001691391,0.0009032823,0.0009660852,0.00002819869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945727,0.0005966044,0.002668862,0.0002475563,0.00007441357,0.0000226436,0.0009843367,0.0000604745,0.0007724004],"genre_scores_gemma":[0.9980253,0.00009559966,0.0008943296,0.00002087001,0.00005125926,0.000009572889,0.00069631,0.000002573215,0.0002041993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003503612,"threshold_uncertainty_score":0.006966472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02173553268325803,"score_gpt":0.2681421664821823,"score_spread":0.2464066337989242,"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."}}