{"id":"W2791162515","doi":"10.1093/jamia/ocx153","title":"A snapshot of health information exchange across five nations: an investigation of frontline clinician experiences in emergency care","year":2017,"lang":"en","type":"article","venue":"Journal of the American Medical Informatics Association","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical School, University of Michigan; University of Michigan","keywords":"Health information exchange; Medicine; SAFER; Thematic analysis; Health care; Medical emergency; Information exchange; Nursing; Family medicine; Qualitative research; Health information","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01136356,0.0003409443,0.0004686567,0.001712812,0.008715041,0.005850862,0.001326887,0.001848754,0.003132204],"category_scores_gemma":[0.0267875,0.000765375,0.0003119891,0.00201961,0.004784209,0.007694723,0.009471257,0.002725085,0.0002747335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006012708,"about_ca_system_score_gemma":0.005951975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01905439,"about_ca_topic_score_gemma":0.03347146,"domain_scores_codex":[0.9875005,0.009352434,0.0006695198,0.0005017651,0.0006531808,0.001322504],"domain_scores_gemma":[0.9780578,0.01184611,0.003685873,0.0008390439,0.002130392,0.003440808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003452231,0.00003323884,0.01449504,0.0001082895,0.000005936242,0.00108999,0.9789661,0.00001816109,0.0001887427,0.0004983449,0.0007538144,0.003807855],"study_design_scores_gemma":[0.000002609256,0.0000375035,0.006460852,0.00009811632,0.000002590838,0.0003477912,0.9897854,0.00003246215,0.00005100987,0.0000768567,0.003096172,0.000008734486],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928944,0.0006085085,0.0004467542,0.002489682,0.00003189993,0.00004942756,0.0001091917,0.00001158026,0.00335858],"genre_scores_gemma":[0.9970443,0.0006329513,0.0005724445,0.001059794,0.00001183799,0.00005427601,0.00008443456,0.00001171609,0.0005281414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01905439,"threshold_uncertainty_score":0.06009692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05706170413230097,"score_gpt":0.4790597728240273,"score_spread":0.4219980686917263,"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."}}