{"id":"W2980969178","doi":"10.1007/s12630-019-01511-8","title":"Potential impact of changes in administrative database coding methodology on research and policy decisions: an example from the Ontario Health Insurance Plan","year":2019,"lang":"en","type":"letter","venue":"Canadian Journal of Anesthesia/Journal canadien d anesthésie","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute for Clinical Evaluative Sciences; Queen's University","funders":"Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences","keywords":"Plan (archaeology); Coding (social sciences); Health plan; Health insurance; Business; Database; Actuarial science; Computer science; Health care; Geography; Economics; Sociology; Economic growth","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01527664,0.000445614,0.001486617,0.00236333,0.001668008,0.0001105338,0.001136284,0.001007469,0.0004055141],"category_scores_gemma":[0.001997985,0.0003087407,0.000163722,0.0005837711,0.0004384235,0.0003750635,0.00003257343,0.01279626,0.000011156],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.005993516,"about_ca_system_score_gemma":0.07471567,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9290729,"about_ca_topic_score_gemma":0.9382788,"domain_scores_codex":[0.9889377,0.005468027,0.002175473,0.0003836435,0.001139614,0.001895558],"domain_scores_gemma":[0.9866911,0.00678314,0.002683755,0.0006143287,0.00102953,0.002198206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"case_report","study_design_scores_codex":[0.001792817,0.00006463288,0.06427312,0.000494655,0.0002428564,0.1521193,0.1189472,0.0001296457,0.000006109443,0.0004809167,0.6544839,0.006964858],"study_design_scores_gemma":[0.005783201,0.01884347,0.342946,0.016844,0.00008709688,0.3587869,0.02346894,0.00008788801,0.000003859908,0.003686302,0.228395,0.001067251],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7167883,0.0005962981,0.00002030834,0.2810366,0.0005422336,0.0006703926,0.0002342731,0.00000351463,0.0001080853],"genre_scores_gemma":[0.8789269,0.001613132,0.001035886,0.1065773,0.01051096,0.00002811852,0.0005446429,0.0001285707,0.0006345178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4260888,"threshold_uncertainty_score":0.9999365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4963921500503896,"score_gpt":0.480104377529927,"score_spread":0.0162877725204626,"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."}}