{"id":"W2157817782","doi":"10.5600/mmrr.002.01.a01","title":"Emergency Department Utilization in the Texas Medicaid Emergency Waiver","year":2011,"lang":"en","type":"article","venue":"Medicare & Medicaid Research Review","topic":"Disaster Response and Management","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centers for Medicare and Medicaid Services","keywords":"Medicaid; Emergency department; Waiver; Poisson regression; Ethnic group; Medicine; Demography; Family medicine; Medical diagnosis; Outreach; Quarter (Canadian coin); Descriptive statistics; Government (linguistics); Emergency medicine; Medical emergency; Gerontology; Environmental health; Geography; Health care; Population; Political science; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001090786,0.0001279532,0.0001147479,0.000965628,0.0001919815,0.0003976424,0.0003716653,0.0001842072,0.001803051],"category_scores_gemma":[0.003321547,0.00009222455,0.0001977188,0.001050786,0.0001014934,0.0002736392,0.0004174451,0.0002934615,0.0002347058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001316327,"about_ca_system_score_gemma":0.001683285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04693787,"about_ca_topic_score_gemma":0.06213255,"domain_scores_codex":[0.999213,0.0002223039,0.00008182447,0.00009218111,0.0002645188,0.0001261363],"domain_scores_gemma":[0.9978628,0.0003151444,0.001208494,0.00003116257,0.0004233733,0.0001590716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006797056,0.00009680189,0.9837152,0.00008708586,0.00005318686,0.00008962194,0.0001670274,0.0004438504,0.00009577909,0.00009674983,0.004271635,0.01081514],"study_design_scores_gemma":[0.000007732447,0.00005817121,0.9968912,0.00004615223,0.00001320625,0.00006336334,0.0003065774,0.0004444478,0.00006277002,0.00001673812,0.002086852,0.000002872529],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892791,0.0006211922,0.0001858303,0.0006025896,0.0000118899,0.00007955745,0.005494917,0.00001601419,0.003708913],"genre_scores_gemma":[0.9890183,0.0006531724,0.0003880051,0.0003017617,0.00003442612,0.000169912,0.007644118,0.000003276004,0.001787094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04693787,"threshold_uncertainty_score":0.09332937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5015281935408319,"score_gpt":0.5489578977645055,"score_spread":0.04742970422367365,"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."}}