{"id":"W2606901347","doi":"10.23889/ijpds.v1i1.72","title":"Comparison of Risk Adjustment Methods in Patients with Liver Disease Using Electronic Medical Record","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Akaike information criterion; Medicine; Cohort; Cirrhosis; Liver disease; Logistic regression; Statistic; Internal medicine; Medical record; Emergency medicine; Statistics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002646675,0.0000634941,0.0001910397,0.0002637889,0.0002845841,0.0001223317,0.001293647,0.00003299547,0.00004062853],"category_scores_gemma":[0.001532992,0.0000489299,0.00003109072,0.0000763853,0.00009219831,0.001374127,0.0001810121,0.0001553209,0.00000217501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003091391,"about_ca_system_score_gemma":0.0001847512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005040202,"about_ca_topic_score_gemma":0.0006551311,"domain_scores_codex":[0.9985934,0.00002192603,0.000674809,0.0002492404,0.0002694907,0.0001911691],"domain_scores_gemma":[0.9980014,0.00002512974,0.001260017,0.0003789046,0.0001936206,0.0001409143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005651237,0.00007114565,0.9424204,0.000005556316,0.00001145548,4.751708e-7,0.00004348108,0.0001511794,4.567815e-7,0.006034116,0.000008065347,0.05119722],"study_design_scores_gemma":[0.0005375728,0.00004315014,0.9034695,0.00006365878,0.000001988325,0.000001289794,0.00001115482,0.09248453,0.000001577753,0.002492595,0.0008310141,0.00006193227],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495164,0.0002004175,0.04762708,0.0001807985,0.001891708,0.0001752565,0.0003665223,0.000002589414,0.00003930468],"genre_scores_gemma":[0.9874378,0.00008900095,0.0122351,0.00001891879,0.0001432615,0.000001963163,0.00005928705,0.000005567876,0.000009055789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09233335,"threshold_uncertainty_score":0.7619311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1615232314019049,"score_gpt":0.4700567759527047,"score_spread":0.3085335445507998,"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."}}