{"id":"W2891268533","doi":"10.71781/665","title":"Développement d’un algorithme pour la surveillance de l’incidence du cancer colorectal à Montréal avec les banques données médico-administratives de la RAMQ","year":2017,"lang":"fr","type":"dissertation","venue":"Open MIND","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Colorectal cancer; Political science; Humanities; Gynecology; Cancer; Medicine; Art; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"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":[0.006646311,0.001595151,0.001396444,0.00294066,0.001215608,0.003468689,0.002738797,0.001486615,0.004024222],"category_scores_gemma":[0.02407574,0.0009158045,0.001750333,0.002064727,0.0007750338,0.001392416,0.001643214,0.001725654,0.001209476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005058717,"about_ca_system_score_gemma":0.01167302,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3612392,"about_ca_topic_score_gemma":0.2534957,"domain_scores_codex":[0.997134,0.0007822336,0.0002742587,0.0009491032,0.000570043,0.0002904235],"domain_scores_gemma":[0.9920248,0.003926901,0.0004178631,0.0004137423,0.003011544,0.0002052575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008555746,0.0003563932,0.08016215,0.0006306127,0.001070742,0.0003729495,0.0008523716,0.2911931,0.005624491,0.005627981,0.01361676,0.5996369],"study_design_scores_gemma":[0.0002626815,0.000143512,0.01540119,0.0001039382,0.0001527922,0.0001402826,0.0002147681,0.9706834,0.003629469,0.002527605,0.00667108,0.00006933311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06779626,0.0008684627,0.9165499,0.001678824,0.0001877708,0.001233537,0.002558708,0.006517236,0.002609314],"genre_scores_gemma":[0.1878202,0.0003177963,0.8037587,0.0004444183,0.00006490241,0.0009573608,0.003250014,0.0002721648,0.00311437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6387608,"threshold_uncertainty_score":0.7182732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02907468547312032,"score_gpt":0.3438977623231068,"score_spread":0.3148230768499865,"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."}}