{"id":"W2897631672","doi":"10.2196/10870","title":"Validation and Testing of Fast Healthcare Interoperability Resources Standards Compliance: Data Analysis","year":2018,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interoperability; Computer science; Conformance testing; Implementation; Health care; Software engineering; Semantic interoperability; Data science; Database; World Wide Web; Standardization; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006466895,0.0001495902,0.0006118531,0.0001771366,0.0004687299,0.00001434682,0.0005530079,0.0002890916,0.0003602788],"category_scores_gemma":[0.002445016,0.0001119171,0.0000315666,0.0009334825,0.0003721532,0.0003053115,0.0005462277,0.0008306322,0.00003026425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002981792,"about_ca_system_score_gemma":0.001508124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001027327,"about_ca_topic_score_gemma":0.0009668852,"domain_scores_codex":[0.9953887,0.0006860251,0.001985041,0.0002013931,0.001192415,0.0005463801],"domain_scores_gemma":[0.9958566,0.0008832709,0.0007994951,0.0009680454,0.001053984,0.0004386291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001811303,0.0001375588,0.6189727,0.01853835,0.0003922964,0.00000133064,0.1646381,0.000001084254,0.00002746676,0.0004682039,0.01323176,0.18341],"study_design_scores_gemma":[0.005148703,0.00318196,0.1377699,0.01313717,0.0005519769,0.00003232623,0.17404,0.458448,0.0001699253,0.000620119,0.2057799,0.001120017],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870805,0.000111963,0.006391912,0.001271829,0.0002887176,0.0009105516,0.0003842089,0.00009689023,0.003463396],"genre_scores_gemma":[0.9952993,0.00003221439,0.003092044,0.0009596119,0.0003447473,0.00004668952,0.0001505625,0.00001207299,0.00006271475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4812027,"threshold_uncertainty_score":0.4563846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1910867284771592,"score_gpt":0.5154672799794426,"score_spread":0.3243805515022835,"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."}}