{"id":"W2895747123","doi":"10.23889/ijpds.v3i3.433","title":"The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health Promotion and Cardiovascular Prevention","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Alberta Health; University of Calgary; University of Alberta; Manitoba Health; Public Health Agency of Canada; Health PEI; Institute for Clinical Evaluative Sciences; Government of Nunavut; Government of Northwest Territories; Nova Scotia Health Authority; Government of New Brunswick; Nova Scotia Department of Health and Wellness; Veterans Affairs Canada; Government of Saskatchewan; Ministry of Health; Institut National de Santé Publique du Québec; University of Manitoba","funders":"Government of Canada; Ministry of Health, Saskatchewan; Public Health Agency; Public Health Agency of Canada","keywords":"Disease surveillance; Disease registry; Public health; Disease; Chronic disease; Population; Medicine; Agency (philosophy); Environmental health; Business; Family medicine","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":[0.02584943,0.001665363,0.001363157,0.008399317,0.003686586,0.007592561,0.007122103,0.002251844,0.004398089],"category_scores_gemma":[0.04795746,0.001093526,0.001845577,0.0148728,0.002931517,0.004183734,0.004717375,0.003073502,0.001410213],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05954384,"about_ca_system_score_gemma":0.127882,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9356747,"about_ca_topic_score_gemma":0.9174882,"domain_scores_codex":[0.9697136,0.01264772,0.001925522,0.004513049,0.009537071,0.001663131],"domain_scores_gemma":[0.9698644,0.006659883,0.001879185,0.002433867,0.01715973,0.002002925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001911195,0.0001531882,0.04025028,0.001374189,0.0006462957,0.0003962637,0.002747438,0.07587118,0.0003307953,0.4170047,0.2461991,0.2148354],"study_design_scores_gemma":[0.0002974647,0.0001881706,0.02325297,0.001521428,0.000405912,0.0004049416,0.001834102,0.212208,0.0003501748,0.1709255,0.5881926,0.0004188358],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01333763,0.009799473,0.6677287,0.08247857,0.002284438,0.008527362,0.0738344,0.005203753,0.1368057],"genre_scores_gemma":[0.224667,0.01281411,0.6875749,0.00678511,0.0009533507,0.005920989,0.04279032,0.000556418,0.0179378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9404562,"threshold_uncertainty_score":0.4320229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07300541383426135,"score_gpt":0.4097254394438772,"score_spread":0.3367200256096159,"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."}}