{"id":"W2804792234","doi":"10.23889/ijpds.v3i1.450","title":"Unlocking First Nations health information through data linkage","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Laurentian University; Institute for Work & Health; Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences","funders":"Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences","keywords":"Indigenous; Linkage (software); Sovereignty; Context (archaeology); Linked data; Population; Record linkage; Geography; Metis; Economic growth; Database; Political science; Medicine; Environmental health; Biology; Law; Genetics; Ecology; World Wide Web; Computer science; Economics; Politics","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":[0.1725081,0.0007700245,0.001424336,0.01438826,0.004354548,0.009389689,0.005243065,0.001973264,0.007606579],"category_scores_gemma":[0.3007473,0.0008342699,0.001369627,0.03057709,0.004445591,0.008814375,0.0176884,0.00250843,0.001741021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01223878,"about_ca_system_score_gemma":0.07005542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09804869,"about_ca_topic_score_gemma":0.07777833,"domain_scores_codex":[0.8029892,0.1377026,0.0166441,0.01157197,0.02858134,0.002510847],"domain_scores_gemma":[0.6860916,0.1545038,0.04350949,0.06188026,0.0497499,0.004265008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002870361,0.0001587751,0.1145356,0.007131464,0.0008839451,0.0004321223,0.03087862,0.004930843,0.0007883057,0.1904878,0.0650557,0.5844297],"study_design_scores_gemma":[0.0001526682,0.0002035215,0.06163185,0.01763328,0.0006687419,0.0007895524,0.01620658,0.01428858,0.002592639,0.1794426,0.7060558,0.0003342094],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06132248,0.01695882,0.7104252,0.06452769,0.001428979,0.007167888,0.04096789,0.002271056,0.09492999],"genre_scores_gemma":[0.2847131,0.01030997,0.6536589,0.006123816,0.0007618305,0.00845784,0.02855674,0.0005674926,0.006850136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1725081,"threshold_uncertainty_score":0.9123207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4724617458589112,"score_gpt":0.5651324642231068,"score_spread":0.09267071836419566,"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."}}