{"id":"W3040746161","doi":"10.1002/cam4.3241","title":"Body mass index trajectories and prostate cancer risk: Results from the EPICAP study","year":2020,"lang":"en","type":"article","venue":"Cancer Medicine","topic":"Cancer Risks and Factors","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du Travail; Fondation de France; Ligue Contre le Cancer; Institute of Cancer Research; Institut National de la Santé et de la Recherche Médicale","keywords":"Prostate cancer; Body mass index; Overweight; Medicine; Obesity; Prostate; Cancer; Epidemiology; Oncology; Internal medicine; Gynecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002427932,0.0002753296,0.0006007978,0.00003445476,0.0001625139,0.00001988559,0.0001496686,0.00007365151,0.0005446023],"category_scores_gemma":[0.0004099901,0.0001535195,0.00004889752,0.0003687943,0.000336423,0.00006879597,0.00005201761,0.000554533,0.000004363076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001195057,"about_ca_system_score_gemma":0.0002403149,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04763913,"about_ca_topic_score_gemma":0.003046374,"domain_scores_codex":[0.9980626,0.00008336514,0.0004680672,0.0005804794,0.0004971355,0.0003083916],"domain_scores_gemma":[0.9986566,0.0002499307,0.0002222193,0.0003820731,0.0001219654,0.0003671614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002795963,0.00004483182,0.9226068,0.00003864381,0.0003257631,0.0000492418,0.02823229,0.00001851128,0.001105741,0.000004044084,0.02723206,0.01754606],"study_design_scores_gemma":[0.009950114,0.001026733,0.9178787,0.0002622364,0.0006565789,0.000001658905,0.008768674,0.0002981206,0.0002337507,0.00004419578,0.06069413,0.0001850757],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9342699,0.01287155,0.00002932838,0.04981548,0.0007601659,0.001209797,0.0006433039,0.00008726966,0.0003131653],"genre_scores_gemma":[0.9842045,0.008400373,0.00001151955,0.00358805,0.00319256,0.0001783225,0.00004145926,0.00003920684,0.000344012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04993457,"threshold_uncertainty_score":0.9587027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03193052428372023,"score_gpt":0.3194039583815524,"score_spread":0.2874734340978322,"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."}}