{"id":"W4385571474","doi":"10.18653/v1/2023.acl-srw.19","title":"Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment","year":2023,"lang":"en","type":"article","venue":"","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"","keywords":"Zhàng; Computer science; Code (set theory); Correlation; Volume (thermodynamics); Association (psychology); Programming language; Natural language processing; Artificial intelligence; Mathematics; Philosophy; History; Physics; China; Archaeology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00239544,0.00006069466,0.0001310989,0.00006762012,0.0005391004,0.0000020401,0.0000917084,0.0001216691,0.0004319219],"category_scores_gemma":[0.001218413,0.00003145145,0.00003397594,0.0002652043,0.00001999743,0.00003834085,0.00005254558,0.0004240274,0.001247778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001164842,"about_ca_system_score_gemma":0.0001068006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004031058,"about_ca_topic_score_gemma":0.00001289358,"domain_scores_codex":[0.9984493,0.0004513883,0.0004440191,0.00007463479,0.0003516905,0.0002289225],"domain_scores_gemma":[0.9977975,0.001700927,0.0002100336,0.0001843886,0.0000390856,0.00006805381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005742656,0.00005476157,0.3083057,0.004400661,0.00003739437,0.000001328901,0.01512452,0.002798844,0.0004160621,0.04038263,0.4609993,0.1669046],"study_design_scores_gemma":[0.005485249,0.001452746,0.6567107,0.004005667,0.00006302736,7.510615e-7,0.002126465,0.1793142,0.002911687,0.001093639,0.1465233,0.0003125998],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9029158,0.00000748009,0.003585545,0.009207114,0.002924736,0.00183159,0.000008297463,0.000280424,0.07923903],"genre_scores_gemma":[0.9925301,0.00001192781,0.00002636057,0.001432008,0.0001148511,0.00007197153,0.00001151598,0.000006140932,0.005795119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.348405,"threshold_uncertainty_score":0.9995298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1684633999674552,"score_gpt":0.4738528473400231,"score_spread":0.3053894473725679,"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."}}