{"id":"W2473187811","doi":"10.2196/humanfactors.5820","title":"Usability Testing of a National Substance Use Screening Tool Embedded in Electronic Health Records","year":2016,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Usability; Workflow; System usability scale; Electronic health record; Documentation; Medicine; Health care; Computer science; Heuristic evaluation; Database; Human–computer interaction","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":[0.03783978,0.0007441491,0.000614099,0.001304041,0.0008835846,0.001708568,0.001197179,0.0007709897,0.001041217],"category_scores_gemma":[0.08455627,0.0006031438,0.001171657,0.000808995,0.0007285671,0.001528937,0.001433383,0.0006643036,0.0002344855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143221,"about_ca_system_score_gemma":0.001826871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00162389,"about_ca_topic_score_gemma":0.002691362,"domain_scores_codex":[0.9656259,0.02414979,0.00413474,0.001283098,0.003921464,0.0008849549],"domain_scores_gemma":[0.8977217,0.07831652,0.005077538,0.004763637,0.01315811,0.0009624044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.008547737,0.02278141,0.2738734,0.005356508,0.0008327006,0.001754464,0.05878897,0.004351498,0.03553026,0.0005121123,0.002832017,0.5848387],"study_design_scores_gemma":[0.002565489,0.156909,0.7062569,0.003249935,0.001642795,0.00234393,0.04292953,0.02450455,0.04345339,0.0005447376,0.01501806,0.0005818145],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916618,0.00007702848,0.004935468,0.000101735,0.0000305332,0.002084939,0.00007920161,0.0001273004,0.0009020197],"genre_scores_gemma":[0.9592155,0.0001389562,0.03721378,0.0001404119,0.00002899026,0.002442459,0.0002290137,0.00003275149,0.0005580157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03783978,"threshold_uncertainty_score":0.2001183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2036661398255152,"score_gpt":0.4582587000225307,"score_spread":0.2545925601970156,"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."}}