{"id":"W4280506342","doi":"10.2196/32168","title":"Integrated Health Record Viewers and Reduction in Duplicate Medical Imaging: Retrospective Observational Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Department of Veterans Affairs","keywords":"Veterans Affairs; Health care; Health information exchange; Medical record; Medicine; Medical imaging; Observational study; Medical emergency; Radiology; Health information","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":[0.007776893,0.0003550386,0.0006601152,0.002917324,0.001039761,0.001395783,0.001390706,0.0007215711,0.002329114],"category_scores_gemma":[0.02705298,0.00106102,0.001563322,0.005164509,0.000804854,0.001724317,0.001648223,0.001957459,0.0003925504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001826494,"about_ca_system_score_gemma":0.002594214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0206102,"about_ca_topic_score_gemma":0.01574617,"domain_scores_codex":[0.9899237,0.002971518,0.002432626,0.001489314,0.002354417,0.0008285817],"domain_scores_gemma":[0.9455846,0.0104992,0.03497512,0.003170935,0.00389952,0.001870693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001092953,0.00007730258,0.9986932,0.00004042341,0.00009302435,0.00002676767,0.0001219685,0.00002816714,0.00001680938,0.00002046565,0.0002037421,0.0005689629],"study_design_scores_gemma":[0.00004023847,0.0004207166,0.9967062,0.00009480317,0.0002013165,0.0003486357,0.0009989833,0.000469256,0.000087699,0.00003987826,0.0005760281,0.00001623996],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945247,0.0007387448,0.0004849721,0.0001000431,0.00001190201,0.0002174801,0.003380956,0.00001089204,0.0005304574],"genre_scores_gemma":[0.996552,0.0003315351,0.0006327468,0.0001204984,0.00002159354,0.0002176568,0.001979877,0.000009382379,0.0001347057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0206102,"threshold_uncertainty_score":0.04112858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05672625314373717,"score_gpt":0.4334550450288883,"score_spread":0.3767287918851512,"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."}}