{"id":"W2908319631","doi":"10.2196/11233","title":"Use of Telemedicine to Screen Patients in the Emergency Department: Matched Cohort Study Evaluating Efficiency and Patient Safety of Telemedicine","year":2018,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Healthcare Research and Quality","keywords":"Medicine; Telemedicine; Overcrowding; Triage; Emergency department; Emergency medicine; Medical emergency; Cohort; Health care; Internal medicine; Nursing","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":[0.002033164,0.0002993608,0.0003679949,0.0008420796,0.0003828174,0.0006721892,0.0004923522,0.0005667933,0.001265609],"category_scores_gemma":[0.00610715,0.0004120032,0.0007923821,0.0008085126,0.000288792,0.0006362173,0.0005090602,0.0005766854,0.0002267928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006176873,"about_ca_system_score_gemma":0.0004948241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005832693,"about_ca_topic_score_gemma":0.005352141,"domain_scores_codex":[0.9981493,0.0006199023,0.0001872769,0.0004627938,0.0003342088,0.0002465326],"domain_scores_gemma":[0.9957885,0.001028774,0.001750012,0.0004972598,0.0004464131,0.0004890026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005177615,0.0003100088,0.998004,0.000008615445,0.000119314,0.0000330415,0.0000981063,0.00002904154,0.0001144478,0.000008595075,0.00005376874,0.0007032335],"study_design_scores_gemma":[0.00006360647,0.001202133,0.9977011,0.000005936618,0.00006769085,0.00008604788,0.000330012,0.0003760952,0.00007352096,0.000009121399,0.00007861386,0.000006043446],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996953,0.00002566548,0.00004971688,0.000006927417,0.000003118545,0.00002976248,0.0001010524,9.545937e-7,0.00008764599],"genre_scores_gemma":[0.9996994,0.00002335285,0.00005680263,0.00001962702,0.000006377383,0.00002497206,0.0001139423,0.000001244773,0.00005420584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005832693,"threshold_uncertainty_score":0.01159751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04360161829257764,"score_gpt":0.3893839276913867,"score_spread":0.3457823093988091,"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."}}