{"id":"W4226069305","doi":"10.2196/34681","title":"Identifying Patients With Hypoglycemia Using Natural Language Processing: Systematic Literature Review","year":2022,"lang":"en","type":"review","venue":"JMIR Diabetes","topic":"Diabetes Management and Research","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Hypoglycemia; PsycINFO; Medicine; Artificial intelligence; CINAHL; Natural language processing; Machine learning; MEDLINE; Computer science; Pediatrics; Internal medicine; Psychiatry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009891981,0.001572342,0.006269777,0.01222571,0.0007016162,0.002558911,0.002434277,0.001833182,0.005578089],"category_scores_gemma":[0.06607188,0.0009642178,0.007237915,0.01152908,0.00103993,0.003300362,0.001843537,0.001282793,0.0004419418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004163742,"about_ca_system_score_gemma":0.01718753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008076373,"about_ca_topic_score_gemma":0.02210952,"domain_scores_codex":[0.9899329,0.003410939,0.004104871,0.0007159658,0.001587574,0.0002478276],"domain_scores_gemma":[0.9412776,0.04390932,0.009427305,0.0007030368,0.004329672,0.00035306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00007903805,0.00001395536,0.0006947209,0.9720421,0.003673817,0.0001011812,0.0002399239,0.00007736458,0.00006154556,0.0001204504,0.001198812,0.02169706],"study_design_scores_gemma":[0.0001217072,0.0001152586,0.002121763,0.9610459,0.02704092,0.0003343981,0.000406465,0.00007303807,0.00009386166,0.0002505612,0.008367131,0.00002897232],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001916105,0.9948313,0.0003821774,0.0005482388,0.0001442576,0.0008474563,0.0008982276,0.00001927169,0.000413074],"genre_scores_gemma":[0.01900518,0.9763431,0.001318141,0.001066053,0.00009878273,0.001515943,0.0005152112,0.000009515996,0.0001280223],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01222571,"threshold_uncertainty_score":0.05231446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03884522189674269,"score_gpt":0.3681025190598333,"score_spread":0.3292572971630907,"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."}}