{"id":"W2513150783","doi":"10.1371/journal.pone.0161173","title":"Creating a Powerful Platform to Explore Health in a Correctional Population: A Record Linkage Study","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; Institute for Clinical Evaluative Sciences; St. Michael's Hospital; Sunnybrook Hospital; University of Toronto; Public Health Ontario","funders":"Institute of Gender and Health; Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research; University of Toronto; Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences","keywords":"Medical record; Record linkage; Linkage (software); Health records; Medicine; Population; Health care; Family medicine; Environmental health; Political science; Biology","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":[0.02349289,0.0002824576,0.0005573082,0.007056738,0.004917356,0.003361078,0.001776034,0.0007953016,0.002350903],"category_scores_gemma":[0.06710186,0.0004852462,0.0005961506,0.014641,0.001037489,0.002486727,0.004981558,0.0009118876,0.0003773919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0124412,"about_ca_system_score_gemma":0.03054886,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6064245,"about_ca_topic_score_gemma":0.6944343,"domain_scores_codex":[0.9852653,0.006845389,0.001118888,0.00175475,0.003933193,0.001082596],"domain_scores_gemma":[0.9567342,0.01610335,0.006809481,0.007560491,0.01070269,0.002089865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003464179,0.0005480195,0.821146,0.000773751,0.0004730298,0.0007061502,0.04547452,0.0007166073,0.001011332,0.003817321,0.01193171,0.1130551],"study_design_scores_gemma":[0.0003467289,0.0006805786,0.8427498,0.001340237,0.001149696,0.0006701864,0.05102554,0.006550606,0.002037248,0.002981151,0.09018213,0.0002860978],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9386707,0.001307921,0.02214357,0.003221627,0.00006297429,0.00475723,0.02218016,0.0003545759,0.007301229],"genre_scores_gemma":[0.9197795,0.001080149,0.06323631,0.0006328131,0.00005293966,0.004180705,0.008482493,0.0001148432,0.002440154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6064245,"threshold_uncertainty_score":0.7917867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1742270971418587,"score_gpt":0.3759189291531191,"score_spread":0.2016918320112605,"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."}}