{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.006953926,0.00008709216,0.0001266282,0.0001657659,0.001721931,0.0003465023,0.0007574745,0.00003409986,0.000007452672],"category_scores_gemma":[0.001518434,0.00006465441,0.0000839827,0.0002804338,0.0002087111,0.0006427855,0.00006785048,0.00009491354,0.000009262245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001286398,"about_ca_system_score_gemma":0.003794004,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001328087,"about_ca_topic_score_gemma":0.0693498,"domain_scores_codex":[0.9980913,0.0001106625,0.0003669036,0.0003119383,0.0008047409,0.0003144064],"domain_scores_gemma":[0.9959747,0.00007190333,0.0002102247,0.0004531169,0.002871687,0.0004183937],"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":[0.002885078,0.0003535016,0.1575313,0.0008652179,0.001475349,0.00007171604,0.001310738,0.01555174,0.00108395,0.1991636,0.07034738,0.5493605],"study_design_scores_gemma":[0.00106488,0.00008506674,0.1175108,0.00009965372,0.00001754568,0.00007325894,0.00004845593,0.8400754,0.000008322892,0.0005635703,0.04035642,0.00009654702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03752936,0.0009281366,0.9202446,0.02274238,0.01088198,0.003407102,0.003542496,0.00008573206,0.0006381925],"genre_scores_gemma":[0.9955405,0.00007027762,0.001939911,0.0001901131,0.001278145,0.00003340403,0.0005411329,0.00001070192,0.0003958093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9580112,"threshold_uncertainty_score":0.9995777,"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."}}