{"id":"W4283524809","doi":"10.1016/j.jval.2022.04.1033","title":"HSD32 Using Natural Language Processing (NLP) of Unstructured EMR Data to Describe Canadian Patients with Familial Hypercholesterolemia (FH) and Their Management","year":2022,"lang":"en","type":"article","venue":"Value in Health","topic":"Lipoproteins and Cardiovascular Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Novartis (Canada); St. Michael's Hospital; University of Regina; University of British Columbia","funders":"","keywords":"Medicine; Ezetimibe; Statin; Medical record; Diabetes mellitus; Electronic medical record; Internal medicine; Familial hypercholesterolemia; Natural history; Pediatrics; Cholesterol; Family medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009513638,0.0004193174,0.0002435712,0.002793386,0.001088637,0.001153093,0.0003934289,0.000347884,0.003590377],"category_scores_gemma":[0.006060322,0.0001387368,0.0004620719,0.002665869,0.0002895385,0.0002747481,0.0006231014,0.0004380623,0.0005420357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006791405,"about_ca_system_score_gemma":0.01573162,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8894833,"about_ca_topic_score_gemma":0.9002614,"domain_scores_codex":[0.9994886,0.0000880934,0.00008318448,0.0001028858,0.0001359456,0.0001012971],"domain_scores_gemma":[0.9974836,0.0009857039,0.00021807,0.0001299215,0.001035753,0.00014713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001463029,0.0004296348,0.6170509,0.001543548,0.0002837303,0.008279517,0.02139438,0.0105123,0.02257366,0.005780189,0.07246061,0.2382285],"study_design_scores_gemma":[0.0002192914,0.000216652,0.6927376,0.0005916599,0.0003903282,0.004987061,0.02608201,0.05087241,0.0119276,0.004058622,0.2075938,0.0003229956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7970597,0.0008588398,0.02289998,0.002865897,0.00007787047,0.001562652,0.154313,0.001819885,0.01854215],"genre_scores_gemma":[0.8471906,0.000676758,0.07418319,0.0004695135,0.00003272308,0.000576698,0.07114935,0.0001937349,0.005527303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1105167,"threshold_uncertainty_score":0.2223351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03412514860987251,"score_gpt":0.2711472083511872,"score_spread":0.2370220597413147,"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."}}