{"id":"W3122106231","doi":"","title":"MEASURING THE RELATIONSHIP BETWEEN COSTS AND OUTCOMES: THE EXAMPLE OF ACUTE MYOCARDIAL INFARCTION IN GERMAN HOSPITALS","year":2012,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Myocardial infarction; Medicine; Reimbursement; Proxy (statistics); Emergency medicine; Disease; German; Proportional hazards model; Intensive care medicine; Hazard ratio; Actuarial science; Health care; Internal medicine; Statistics; Confidence interval","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":[0.002908621,0.0004127385,0.0003992411,0.002140701,0.0003339677,0.001047185,0.0005905534,0.0005505683,0.00085813],"category_scores_gemma":[0.01127286,0.0001156676,0.000476243,0.003259677,0.0006326513,0.0006362103,0.0008785625,0.0004208176,0.00006008454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002355901,"about_ca_system_score_gemma":0.0006825026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0381342,"about_ca_topic_score_gemma":0.02372017,"domain_scores_codex":[0.9967068,0.002403172,0.0001413041,0.0001949225,0.0003720336,0.0001819176],"domain_scores_gemma":[0.9928877,0.0049657,0.00117493,0.0003748346,0.000433522,0.0001632291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007343382,0.0003700518,0.7762541,0.000559585,0.0008670295,0.001342006,0.001173203,0.09351269,0.001198652,0.04709006,0.004222094,0.07267629],"study_design_scores_gemma":[0.0001264588,0.0003295217,0.8381745,0.0001679087,0.0003925688,0.000495879,0.001834157,0.1321871,0.002047998,0.01899542,0.005153762,0.00009476226],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848718,0.001261921,0.007840895,0.001218532,0.00001890759,0.00005176651,0.001324897,0.00001639469,0.003394884],"genre_scores_gemma":[0.9970667,0.0002021812,0.002179893,0.00003269129,0.000009918442,0.00001920598,0.0003446963,0.000001869542,0.0001430431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0381342,"threshold_uncertainty_score":0.07582444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3924902488271446,"score_gpt":0.4573170941042369,"score_spread":0.06482684527709237,"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."}}