{"id":"W4214891660","doi":"10.2196/30104","title":"A Data-Driven Algorithm to Recommend Initial Clinical Workup for Outpatient Specialty Referral: Algorithm Development and Validation Using Electronic Health Record Data and Expert Surveys","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; National Institute on Aging","keywords":"Algorithm; Specialty; Referral; Electronic health record; Medicine; Computer science; Health records; Data mining; Health care; Family medicine","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":[0.01979985,0.001160798,0.001887953,0.004276531,0.0006666553,0.001903693,0.001996354,0.001992167,0.001179349],"category_scores_gemma":[0.05680352,0.0006964816,0.001488901,0.00233127,0.0003513515,0.001364903,0.0009236346,0.001628575,0.00044114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001891183,"about_ca_system_score_gemma":0.003301448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01916976,"about_ca_topic_score_gemma":0.01496642,"domain_scores_codex":[0.9929618,0.003503323,0.0009541676,0.001749997,0.000639712,0.000191042],"domain_scores_gemma":[0.9344279,0.05299331,0.00372107,0.001431358,0.00671538,0.0007109602],"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":[0.001504862,0.002471991,0.3559787,0.0008303619,0.001987949,0.0002692463,0.000599368,0.273717,0.001404599,0.00153287,0.009975428,0.3497277],"study_design_scores_gemma":[0.0002787739,0.0003868023,0.01831016,0.00009764517,0.000171346,0.0001431641,0.0001344524,0.9780419,0.0005141804,0.001015987,0.0008711041,0.00003436591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4434364,0.001460898,0.5396198,0.002000718,0.0001643819,0.002959479,0.004996443,0.003626249,0.001735642],"genre_scores_gemma":[0.514263,0.0002811595,0.4788058,0.0004081702,0.00007210326,0.001387939,0.004336521,0.00005065967,0.0003945291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01979985,"threshold_uncertainty_score":0.1047128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1991212203843371,"score_gpt":0.4262307638409381,"score_spread":0.227109543456601,"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."}}