{"id":"W2298141847","doi":"10.1002/cam4.695","title":"Blood lipids and prostate cancer: a Mendelian randomization analysis","year":2016,"lang":"en","type":"article","venue":"Cancer Medicine","topic":"Cancer, Lipids, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"National Cancer Institute; Seventh Framework Programme; University of Bristol; Wellcome; Canadian Institutes of Health Research; National Institute for Health and Care Research; National Institutes of Health; Cancer Research UK; University Hospitals Bristol NHS Foundation Trust; European Commission; Royal Marsden NHS Foundation Trust; Wellcome Trust; Institute of Cancer Research; Medical Research Council","keywords":"Mendelian randomization; Prostate cancer; Odds ratio; Medicine; Single-nucleotide polymorphism; Internal medicine; Prostate; Oncology; Cancer; SNP; Logistic regression; Allele; Endocrinology; Genotype; Biology; Genetics; Genetic variants; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.05803711,0.002243958,0.004152054,0.004164112,0.0009974901,0.001906851,0.001958046,0.0017413,0.009803113],"category_scores_gemma":[0.07451653,0.0009800853,0.006470086,0.003840776,0.001715407,0.00121494,0.001524294,0.001605723,0.0007987132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00116375,"about_ca_system_score_gemma":0.001719224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004295005,"about_ca_topic_score_gemma":0.001645017,"domain_scores_codex":[0.9053142,0.07515271,0.002139759,0.01063297,0.005360658,0.001399653],"domain_scores_gemma":[0.9516871,0.03603744,0.003298983,0.007544509,0.0009608283,0.0004711644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.06251527,0.001751731,0.4425039,0.001861339,0.08635867,0.007566108,0.00186894,0.04288635,0.01678708,0.1039133,0.013786,0.2182013],"study_design_scores_gemma":[0.01454249,0.01122711,0.1699747,0.0003320962,0.02761991,0.006344947,0.0004375663,0.6722757,0.004838509,0.07675733,0.01517427,0.0004754234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4511369,0.002651811,0.5316949,0.0008623138,0.0004037912,0.004077336,0.003927635,0.00187112,0.003374091],"genre_scores_gemma":[0.8011276,0.0006021966,0.1882263,0.0003407194,0.0001522972,0.004884526,0.00148682,0.0002732231,0.00290626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05803711,"threshold_uncertainty_score":0.3069332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00658221835692019,"score_gpt":0.2631162300403799,"score_spread":0.2565340116834597,"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."}}