{"id":"W2605680824","doi":"10.23889/ijpds.v1i1.36","title":"Describing the Linkages of the Citizenship and Immigration Canada Permanent Resident Data and Vital Statistics—Death Registry to Ontario’s Administrative Health Database","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; Canadian Institute for Health Information; Institute for Clinical Evaluative Sciences","funders":"","keywords":"Record linkage; Linkage (software); Database; Immigration; Demography; Geography; Medicine; Computer science; Environmental health; Population; Sociology; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.009332192,0.0002414258,0.0002747157,0.005356562,0.001758876,0.002507912,0.001209116,0.000478588,0.005980279],"category_scores_gemma":[0.04766288,0.0003911684,0.0005231465,0.0152167,0.0003684491,0.001094264,0.001451226,0.0004840059,0.001428952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0214562,"about_ca_system_score_gemma":0.05786921,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9102051,"about_ca_topic_score_gemma":0.9347403,"domain_scores_codex":[0.9904311,0.001989085,0.001785131,0.0009332814,0.004103741,0.0007577407],"domain_scores_gemma":[0.9670301,0.00643603,0.005539312,0.002802218,0.01760851,0.0005838455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002605378,0.000109609,0.4758027,0.001839275,0.000262467,0.0007220149,0.005587073,0.01190689,0.001149563,0.02169441,0.2899859,0.1906795],"study_design_scores_gemma":[0.00007942841,0.00006391401,0.5052025,0.001175552,0.0001347572,0.0002606922,0.003243595,0.01633456,0.00243042,0.001824618,0.4691012,0.0001488052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.159991,0.001428785,0.04756442,0.006125835,0.0003153374,0.00393346,0.7257169,0.001622997,0.05330123],"genre_scores_gemma":[0.48704,0.002734022,0.07807474,0.0009973869,0.0001105964,0.004820542,0.4016303,0.0004154695,0.02417688],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08979493,"threshold_uncertainty_score":0.1806474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3466456399602142,"score_gpt":0.4069664830768868,"score_spread":0.06032084311667257,"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."}}