{"id":"W2997155969","doi":"10.71781/596","title":"Addressing gaps in colorectal cancer screening in Canada : multilevel determinants of screening, pathways to screening inequalities, and program evaluation","year":2018,"lang":"en","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de Recherche du Québec - Santé; Social Sciences and Humanities Research Council of Canada; Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"Colorectal cancer screening; Colorectal cancer; Medicine; Inequality; Cancer screening; Cancer; Gerontology; Internal medicine; Mathematics; Colonoscopy","routes":{"ca_aff":false,"ca_fund":true,"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":[0.01232943,0.0003588274,0.000794955,0.002671725,0.003752542,0.003828881,0.001728,0.001155806,0.003918626],"category_scores_gemma":[0.04772939,0.0003454712,0.001154926,0.006454674,0.001782695,0.001741925,0.005134783,0.001873817,0.0001868064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07655915,"about_ca_system_score_gemma":0.3241861,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9758494,"about_ca_topic_score_gemma":0.985132,"domain_scores_codex":[0.9893265,0.003311216,0.0004515748,0.0005284124,0.00278676,0.003595573],"domain_scores_gemma":[0.9744446,0.007608391,0.003044579,0.0006982478,0.00798724,0.006216881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004428127,0.000563775,0.8173031,0.003049983,0.0006989399,0.0001556397,0.00651282,0.002855157,0.0002369292,0.01187943,0.01570597,0.1405956],"study_design_scores_gemma":[0.0001629456,0.0003517351,0.9453191,0.007054594,0.0008997567,0.00007745001,0.01403687,0.007179601,0.0004692469,0.005258187,0.0191056,0.00008484491],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7669299,0.03493243,0.003664713,0.1485822,0.0003747309,0.001780513,0.009155495,0.000207354,0.03437276],"genre_scores_gemma":[0.9825501,0.007856285,0.003464389,0.003070836,0.00005949767,0.0005591376,0.00101778,0.000019581,0.001402411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07655915,"threshold_uncertainty_score":0.5554781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03798978739557622,"score_gpt":0.277122277690232,"score_spread":0.2391324902946557,"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."}}