{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001081174,0.0001864131,0.000488601,0.0001723808,0.00008558149,0.00005651856,0.00003011872,0.00006816365,0.00002487781],"category_scores_gemma":[0.00001145578,0.0001608839,0.00008905146,0.001017444,0.00003216798,0.0002390146,0.00003635589,0.0001352201,3.202475e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008795745,"about_ca_system_score_gemma":0.0007483323,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01670132,"about_ca_topic_score_gemma":0.2109186,"domain_scores_codex":[0.998648,0.0000520021,0.0002111347,0.0004309163,0.0003312665,0.0003266394],"domain_scores_gemma":[0.9992498,0.00004704716,0.0001532699,0.0001693701,0.0002681452,0.000112397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001106854,0.0001194721,0.9862086,0.0001504372,0.0007082531,0.00006009124,0.000900575,0.009786263,0.0003875027,0.00003397352,0.00001462286,0.001519569],"study_design_scores_gemma":[0.001697214,0.00007590745,0.9485068,0.0007633066,0.002337514,0.000004514694,0.001056936,0.03805791,0.006990338,0.0002266562,0.00002161757,0.0002612479],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853982,0.0129938,0.0002717487,0.0007616691,0.00005131053,0.0003601164,0.00009462664,0.00002278729,0.00004575232],"genre_scores_gemma":[0.9935246,0.004725284,0.0004255245,0.0006143015,0.00006972839,0.0002942853,0.00003494529,0.00002212993,0.0002891608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1942173,"threshold_uncertainty_score":0.9898465,"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."}}