{"id":"W1514828683","doi":"10.1186/1472-6963-6-48","title":"Assessing record linkage between health care and Vital Statistics databases using deterministic methods","year":2006,"lang":"en","type":"article","venue":"BMC Health Services Research","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Economics; University of Calgary","funders":"Canadian Institutes of Health Research; Fondation pour la Recherche Médicale; University of Calgary","keywords":"Linkage (software); Record linkage; Medicine; Database; Population; Identifier; Demography; Statistics; Computer science; Genetics; Biology; Environmental health; Mathematics","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":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02907761,0.0002228915,0.0006724646,0.0007374022,0.001617174,0.001736957,0.001015928,0.00007112267,0.00006711682],"category_scores_gemma":[0.0007506271,0.0001936543,0.0000447458,0.001319741,0.0002322559,0.001090706,0.001385939,0.0004867791,0.00005849738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003430987,"about_ca_system_score_gemma":0.001459172,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02289781,"about_ca_topic_score_gemma":0.01154931,"domain_scores_codex":[0.9863939,0.007163932,0.001600293,0.001075877,0.002557919,0.001208047],"domain_scores_gemma":[0.9878415,0.009303113,0.0005476414,0.00117424,0.0005837851,0.0005497501],"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":[0.00003159494,0.0000852356,0.06656787,0.004511392,0.00001192867,0.00001795711,0.002707824,0.00003174611,0.00002055118,0.002425792,0.001481027,0.9221071],"study_design_scores_gemma":[0.001469416,0.001162887,0.4932311,0.001459607,0.00003501636,0.00001712886,0.1099322,0.03648302,0.00007450288,0.01958869,0.3356272,0.0009193362],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1539268,0.003238847,0.8375663,0.0005014904,0.0003578262,0.001170358,0.002478803,0.00007523243,0.0006842989],"genre_scores_gemma":[0.1787766,0.0001918061,0.8186132,0.0009779938,0.000448179,0.00001953234,0.0007755491,0.00003600322,0.0001612259],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9211878,"threshold_uncertainty_score":0.9997689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5803401570006748,"score_gpt":0.6702429424110904,"score_spread":0.08990278541041563,"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."}}