{"id":"W2988743666","doi":"10.1136/bmjhci-2019-100009","title":"Coding and classifying GP data: the POLAR project","year":2019,"lang":"en","type":"article","venue":"BMJ Health & Care Informatics","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Monash University; HCF Research Foundation","keywords":"SNOMED CT; Computer science; Coding (social sciences); Medical diagnosis; Data science; Population; Analytics; Data mining; Big data; Diagnosis code; Information retrieval; Natural language processing; Terminology; Medicine; Pathology","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":[0.03193102,0.0007338211,0.0005527866,0.00744814,0.001927377,0.003792832,0.001251308,0.0008220393,0.008301218],"category_scores_gemma":[0.1045611,0.0007213518,0.0007969096,0.009120874,0.002991421,0.003229189,0.01023834,0.002162456,0.004251986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003717132,"about_ca_system_score_gemma":0.01584419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02383027,"about_ca_topic_score_gemma":0.01851817,"domain_scores_codex":[0.9736992,0.01708606,0.002301111,0.002240198,0.004140155,0.0005333393],"domain_scores_gemma":[0.9480918,0.02339334,0.00385172,0.009952891,0.01354217,0.001167971],"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":[0.0008457833,0.0002296322,0.05562804,0.003542355,0.0001167784,0.0009707371,0.05931052,0.003548463,0.00649626,0.04566869,0.09905377,0.724589],"study_design_scores_gemma":[0.0004390282,0.0004980538,0.05683605,0.004232149,0.0002191429,0.002076364,0.06418141,0.02731992,0.01373608,0.100318,0.7299142,0.0002295641],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2074828,0.002030222,0.6252398,0.01687017,0.0009515214,0.01859261,0.05971606,0.009825497,0.05929131],"genre_scores_gemma":[0.2075475,0.002447591,0.715475,0.001470895,0.0001770908,0.01071262,0.04759133,0.002353437,0.01222449],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03193102,"threshold_uncertainty_score":0.1688694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3970979486549057,"score_gpt":0.5433169716742404,"score_spread":0.1462190230193347,"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."}}