{"id":"W2903066048","doi":"10.1515/hmbci-2018-0049","title":"Impact of adipose tissue on prostate cancer aggressiveness – analysis of a high-risk population","year":2018,"lang":"en","type":"article","venue":"Hormone Molecular Biology and Clinical Investigation","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Jewish General Hospital; McGill University; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Adipose tissue; Medicine; Prostate cancer; Prostatectomy; Univariate analysis; Internal medicine; Prostate; Cancer; Logistic regression; Oncology; Multivariate analysis; Urology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002297263,0.0001140012,0.0004894623,0.0001451271,0.00003452593,0.000002813348,0.00003000789,0.0001560642,0.00001981923],"category_scores_gemma":[0.0002090489,0.0000805919,0.0001550261,0.0003621592,0.0004241704,0.00002414364,0.00001888313,0.0000903981,0.000001274745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003988364,"about_ca_system_score_gemma":0.00007043056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003061724,"about_ca_topic_score_gemma":0.00009894718,"domain_scores_codex":[0.9988964,0.0001811619,0.0004640453,0.0002709562,0.00007750486,0.0001099383],"domain_scores_gemma":[0.9989349,0.0001053276,0.0004641808,0.0002005062,0.0001837992,0.0001112533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006528566,0.000188649,0.9496775,0.00001158686,0.002321963,0.000003990449,0.00006488286,0.00006746538,0.01539045,0.0005397004,0.00001843978,0.0310625],"study_design_scores_gemma":[0.001250644,0.006367456,0.9557683,0.00007557106,0.002683795,6.802182e-7,0.000003049969,0.00038703,0.03094074,0.00244978,0.000004743072,0.00006823505],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974375,0.001685273,0.0001481582,0.000206203,0.00004763242,0.000303502,0.000150609,0.000009020007,0.00001207868],"genre_scores_gemma":[0.9971436,0.001900318,0.00029967,0.0001226484,0.00003970848,0.00003195801,0.0004486484,0.000007672448,0.000005817873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03099426,"threshold_uncertainty_score":0.4628431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02486338131287349,"score_gpt":0.3966469016223041,"score_spread":0.3717835203094307,"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."}}