{"id":"W4241522336","doi":"10.1002/9781118445112.stat05227.pub2","title":"Administrative Databases","year":2015,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Strengths and weaknesses; Database; Population; Data science; Geography; Computer science; Medicine; Psychology; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.01554035,0.001262643,0.00267167,0.02530349,0.001873031,0.007932,0.005792489,0.00225818,0.1649129],"category_scores_gemma":[0.1190094,0.001174343,0.001684242,0.05419306,0.0006239464,0.004354596,0.004028676,0.002888125,0.0964192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004596173,"about_ca_system_score_gemma":0.02039954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0173808,"about_ca_topic_score_gemma":0.01026372,"domain_scores_codex":[0.9635983,0.008777346,0.01486697,0.004230191,0.007102451,0.001424836],"domain_scores_gemma":[0.888566,0.03269168,0.01633452,0.01995455,0.03831289,0.004140349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002549585,0.00008266043,0.00447123,0.003281979,0.0002565701,0.00009204321,0.0002529483,0.0005282888,0.00007362242,0.01265046,0.9044495,0.07360574],"study_design_scores_gemma":[0.0001998973,0.00003260593,0.007872341,0.002396719,0.0001039774,0.0001468945,0.0003141868,0.0005864058,0.0001890602,0.007485753,0.9806212,0.00005099091],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.001220041,0.002192202,0.0057139,0.001580755,0.0004586577,0.001673223,0.9356633,0.001471757,0.05002618],"genre_scores_gemma":[0.0101533,0.003417171,0.014456,0.001672157,0.0004547678,0.005137344,0.9503433,0.0006730772,0.01369295],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1649129,"threshold_uncertainty_score":0.5516886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2287353875103928,"score_gpt":0.4696409827370064,"score_spread":0.2409055952266136,"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."}}