{"id":"W4290188458","doi":"10.2196/40064","title":"Patient Experience and Feedback After Using an Electronic Health Record–Integrated COVID-19 Symptom Checker: Survey Study","year":2022,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Drug Abuse; National Center for Advancing Translational Sciences; University of California, San Francisco; Agency for Healthcare Research and Quality; National Institutes of Health","keywords":"Triage; Hotline; Coronavirus disease 2019 (COVID-19); Demographics; Medicine; Schedule; Computer science; Medical emergency; Psychology; Disease; Infectious disease (medical specialty)","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":[0.004688037,0.0002300693,0.0003854712,0.001032176,0.0006882498,0.0008525107,0.0003114847,0.0007143213,0.001967663],"category_scores_gemma":[0.01317266,0.0002726296,0.0007171883,0.000735799,0.0004576796,0.001025801,0.0009585338,0.0006948062,0.0005300465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007346373,"about_ca_system_score_gemma":0.0005976525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003554061,"about_ca_topic_score_gemma":0.003692487,"domain_scores_codex":[0.9969612,0.001573028,0.0004142863,0.0002047804,0.0004645361,0.0003821529],"domain_scores_gemma":[0.9884511,0.004100762,0.003115958,0.0003475354,0.002252847,0.001731842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003082375,0.0007500978,0.9725729,0.0001149803,0.0000651284,0.0002525979,0.01274592,0.0001074469,0.0004946443,0.00002861451,0.0006749493,0.01188431],"study_design_scores_gemma":[0.00005059656,0.003760197,0.9678749,0.00007593821,0.00005569328,0.0007132936,0.02325965,0.00106685,0.0005702578,0.00002979787,0.002478406,0.00006438336],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989932,0.00003623248,0.0001301617,0.00008918991,0.000003932411,0.0000510132,0.0002756467,0.000006309604,0.0004141441],"genre_scores_gemma":[0.9986389,0.00007717545,0.0003430031,0.0001937994,0.000009347758,0.00009510828,0.0003002739,0.000004602337,0.0003376481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004688037,"threshold_uncertainty_score":0.02479303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1358168380381516,"score_gpt":0.4743876575316035,"score_spread":0.3385708194934519,"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."}}