{"id":"W4408039142","doi":"10.21037/tcr-2025-118","title":"A novel machine learning-driven immunogenic cell death signature for predicting ovarian cancer prognosis","year":2025,"lang":"en","type":"article","venue":"Translational Cancer Research","topic":"Ferroptosis and cancer prognosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"","keywords":"Signature (topology); Ovarian cancer; Oncology; Cancer; Medicine; Internal medicine; Cancer research; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007485503,0.0002323069,0.0003661641,0.0003696011,0.0005493456,0.00006889356,0.0002324753,0.0002247448,0.001162105],"category_scores_gemma":[0.00006888342,0.0002090043,0.0002523688,0.0009627304,0.0001177192,0.000114991,0.00004737097,0.001084809,0.00000532457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003505043,"about_ca_system_score_gemma":0.001741253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002973334,"about_ca_topic_score_gemma":0.0009305797,"domain_scores_codex":[0.9972881,0.00009756723,0.0003903454,0.0006181927,0.000939737,0.0006660713],"domain_scores_gemma":[0.9983232,0.0003339724,0.00006984506,0.0002126374,0.0009087896,0.0001515292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005170313,0.001016361,0.6914359,0.002354348,0.00115856,0.000005478148,0.001219995,0.006942951,0.2363778,0.002061832,0.003885337,0.04837114],"study_design_scores_gemma":[0.02965655,0.002143831,0.4335834,0.003799124,0.001538886,0.00001464365,0.0004522902,0.1314529,0.1671133,0.0009513788,0.228058,0.001235654],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7297257,0.1248181,0.01992339,0.091114,0.001144921,0.01340182,0.00338544,0.0005544546,0.01593212],"genre_scores_gemma":[0.9851836,0.001500353,0.002478852,0.0003232447,0.0003957222,0.004155176,0.0002564497,0.00005934666,0.005647287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2578525,"threshold_uncertainty_score":0.999751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08209265672416796,"score_gpt":0.400590715235368,"score_spread":0.3184980585112001,"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."}}