{"id":"W7098004349","doi":"","title":"RESEARCH ARTICLE Open Access Metabolic syndrome and prostate cancer risk in a population-based case–control","year":2016,"lang":"en","type":"article","venue":"","topic":"Metabolism, Diabetes, and Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prostate cancer; Metabolic syndrome; Dyslipidemia; Odds ratio; Logistic regression; Anthropometry; Cancer; Confidence interval; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00293043,0.0003147133,0.000510334,0.001113216,0.0005645878,0.001151374,0.0008004012,0.0007172744,0.006655094],"category_scores_gemma":[0.006167104,0.0003216971,0.0006527785,0.001609775,0.0003818549,0.0003194898,0.0004418452,0.000418825,0.0006571794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003212785,"about_ca_system_score_gemma":0.000476465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008483366,"about_ca_topic_score_gemma":0.00517976,"domain_scores_codex":[0.9979132,0.0008894955,0.0001948787,0.0005271679,0.0003349826,0.0001402516],"domain_scores_gemma":[0.9978879,0.0005460613,0.0005877662,0.0004359247,0.0003347707,0.0002076083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009755744,0.0003475545,0.986649,0.0001146025,0.001264079,0.0005377986,0.0001952557,0.00008072923,0.0007015155,0.0002038693,0.001117442,0.00781263],"study_design_scores_gemma":[0.0002977003,0.0005378159,0.9938056,0.00003417028,0.0004864161,0.001434062,0.0001163248,0.0004866706,0.0001082131,0.0001251125,0.002554232,0.00001361932],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990849,0.002700902,0.002078719,0.000275129,0.0001180896,0.0002268532,0.001667446,0.00004349338,0.002040406],"genre_scores_gemma":[0.9945634,0.0008005686,0.00125515,0.0001789807,0.00021473,0.0001891981,0.001681729,0.0000126997,0.001103585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008483366,"threshold_uncertainty_score":0.02226353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03179966682853835,"score_gpt":0.3776277510855496,"score_spread":0.3458280842570112,"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."}}