{"id":"W4400895620","doi":"10.2196/48407","title":"Standardizing Corneal Transplantation Records Using openEHR: Case Study","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Standardization; Health care; Medicine; Interoperability; Transplantation; Quality (philosophy); Process (computing); Computer science; Surgery; World Wide Web","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":[0.008012983,0.0004507549,0.0003375172,0.002182503,0.003161896,0.003108905,0.002121938,0.003462951,0.002009736],"category_scores_gemma":[0.03161979,0.0003888237,0.0009514812,0.003057138,0.002012927,0.002279617,0.003137528,0.002542318,0.0005171219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003402701,"about_ca_system_score_gemma":0.003233612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006023131,"about_ca_topic_score_gemma":0.008459454,"domain_scores_codex":[0.9904101,0.004686146,0.001272078,0.0006052023,0.002232069,0.0007945006],"domain_scores_gemma":[0.9721054,0.01555644,0.004122438,0.003506989,0.002660726,0.002047952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006498426,0.004831312,0.2461523,0.00133781,0.0001588406,0.472618,0.07197411,0.005172597,0.004904724,0.01079213,0.009521329,0.171887],"study_design_scores_gemma":[0.000318732,0.002763627,0.1187534,0.00153399,0.0003384833,0.5554951,0.1531549,0.02571782,0.02796041,0.007859728,0.1056722,0.0004316237],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9692125,0.00111563,0.0184532,0.003468876,0.00009764014,0.0005967083,0.0002771273,0.0001620076,0.006616344],"genre_scores_gemma":[0.9732598,0.001415662,0.02202297,0.0007171704,0.00007067344,0.0002345297,0.0003090842,0.00006849396,0.001901585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008012983,"threshold_uncertainty_score":0.04237717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1045535625175573,"score_gpt":0.5062582695246974,"score_spread":0.4017047070071401,"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."}}