{"id":"W4239439642","doi":"10.1002/0470011815.b2a04001","title":"Administrative Databases","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Biostatistics","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Health care; Database; Medicine; Geography; Data science; Computer science; Political science","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":[0.009981784,0.001271248,0.001912191,0.01751455,0.001358294,0.008124582,0.004896195,0.0020879,0.130403],"category_scores_gemma":[0.06714773,0.001014469,0.001331262,0.04239109,0.0004229352,0.003613753,0.002574261,0.002419591,0.09468943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003330532,"about_ca_system_score_gemma":0.01249603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01444716,"about_ca_topic_score_gemma":0.007000977,"domain_scores_codex":[0.9797743,0.004656704,0.006893309,0.00274568,0.005094163,0.0008358554],"domain_scores_gemma":[0.9386161,0.01591777,0.009219233,0.01250597,0.02135278,0.00238825],"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":[0.0002075171,0.00008373264,0.003928789,0.001720734,0.0001988217,0.00009278386,0.0001410221,0.0007553237,0.00008522385,0.01299286,0.8954207,0.0843726],"study_design_scores_gemma":[0.0001838132,0.00002813912,0.007540347,0.0009808774,0.0000733811,0.0001687779,0.000170553,0.0007678178,0.0002136843,0.006272881,0.9835626,0.00003704561],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001319723,0.001833185,0.006639488,0.001224185,0.0003381666,0.001052659,0.9300957,0.001832022,0.05566477],"genre_scores_gemma":[0.009042588,0.00228596,0.01359296,0.001272122,0.0003128188,0.00285054,0.953196,0.0005520656,0.01689486],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.130403,"threshold_uncertainty_score":0.4362415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06730857163352068,"score_gpt":0.3184746169952354,"score_spread":0.2511660453617148,"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."}}