{"id":"W2313622815","doi":"10.1097/00004479-200207000-00002","title":"Outpatient Encounter Data for Risk Adjustment","year":2002,"lang":"en","type":"article","venue":"Journal of Ambulatory Care Management","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Victoria Park","funders":"","keywords":"Payment; Incentive; Audit; Medical diagnosis; Business; Health care; Actuarial science; Quality (philosophy); Data quality; Service (business); Medical emergency; Medicine; Finance; Marketing; Economics; Accounting","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":[0.01941054,0.0007961076,0.001535692,0.006467046,0.0007473806,0.00309515,0.001907146,0.0008986575,0.0170888],"category_scores_gemma":[0.2045987,0.000649645,0.001795059,0.01130582,0.0003336087,0.002621311,0.002138976,0.002514509,0.005611478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00122015,"about_ca_system_score_gemma":0.002986552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01849452,"about_ca_topic_score_gemma":0.007471502,"domain_scores_codex":[0.9749271,0.01310813,0.004118922,0.001871553,0.005240336,0.0007338323],"domain_scores_gemma":[0.8919697,0.05124815,0.01446041,0.02334741,0.01734198,0.001632319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001239964,0.0005453192,0.3582729,0.0008524608,0.001200189,0.0001794338,0.0006892475,0.005742722,0.0005340753,0.01597285,0.1359324,0.4788384],"study_design_scores_gemma":[0.0006705729,0.001048969,0.6047548,0.001677314,0.001007157,0.001185696,0.001386416,0.06021447,0.003342943,0.03375,0.2906883,0.000273398],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1729757,0.008011073,0.4210993,0.01799436,0.003800431,0.006268763,0.2798772,0.009208297,0.08076486],"genre_scores_gemma":[0.5658034,0.002761576,0.2743478,0.002059519,0.00172188,0.003752928,0.1364923,0.001697892,0.01136266],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01941054,"threshold_uncertainty_score":0.102654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08602176242565995,"score_gpt":0.4077485946527339,"score_spread":0.321726832227074,"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."}}