{"id":"W3142995749","doi":"10.1186/s12885-021-08646-2","title":"Geographic disparities in Saskatchewan prostate cancer incidence and its association with physician density: analysis using Bayesian models","year":2021,"lang":"en","type":"article","venue":"BMC Cancer","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Prostate Cancer Fight Foundation","keywords":"Incidence (geometry); Demography; Medicine; Prostate cancer; Statistic; Geography; Cancer; Statistics; Internal medicine; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.007924431,0.0007129911,0.001067637,0.002354263,0.001171797,0.001563196,0.001652766,0.0009204811,0.00442469],"category_scores_gemma":[0.01467412,0.0005893908,0.002718404,0.003398973,0.001011286,0.0006159595,0.001656199,0.001338079,0.0004633008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004588002,"about_ca_system_score_gemma":0.00631607,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5534317,"about_ca_topic_score_gemma":0.4434028,"domain_scores_codex":[0.9954839,0.002932689,0.0001856997,0.0006428831,0.0002925895,0.0004621901],"domain_scores_gemma":[0.9886419,0.007216308,0.001479771,0.001037076,0.001147322,0.0004775749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000229409,0.0000957868,0.9438977,0.00006176008,0.00154506,0.0002417896,0.0006248046,0.03249618,0.0001914404,0.004992992,0.002157107,0.01346592],"study_design_scores_gemma":[0.00008049923,0.0001854256,0.581479,0.0001550894,0.0007791535,0.0002199377,0.001722216,0.4032502,0.0001403855,0.007936785,0.003961446,0.00008997905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754769,0.0007483824,0.01752128,0.001132254,0.00003728329,0.000171179,0.003140227,0.0001115016,0.001660953],"genre_scores_gemma":[0.9904802,0.0004387308,0.005199055,0.0001326901,0.00002106476,0.0001537527,0.001947904,0.00002129882,0.001605397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4465683,"threshold_uncertainty_score":0.8983965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01845492570056981,"score_gpt":0.2770818437742104,"score_spread":0.2586269180736406,"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."}}