{"id":"W3154894801","doi":"10.1055/s-0041-1726491","title":"How to Improve Information Technology to Support Healthcare to Address the COVID-19 Pandemic: an International Survey with Health Informatics Experts","year":2021,"lang":"en","type":"article","venue":"Yearbook of Medical Informatics","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of British Columbia; Alberta Health Services; Toronto Metropolitan University","funders":"Academy of Finland","keywords":"Interoperability; Health informatics; Health care; Telehealth; Informatics; Pandemic; Software deployment; Telemedicine; Information and Communications Technology; Knowledge management; Computer science; Medicine; World Wide Web; Coronavirus disease 2019 (COVID-19); Engineering; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00248253,0.0002125228,0.0005020091,0.0005370774,0.0001296565,0.00007668383,0.0004898026,0.0002023532,0.0001762876],"category_scores_gemma":[0.003270598,0.0001460077,0.00003833286,0.0008636648,0.00009691789,0.0006156566,0.000270459,0.000407676,0.00003779361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000374676,"about_ca_system_score_gemma":0.003490453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005259314,"about_ca_topic_score_gemma":0.001728875,"domain_scores_codex":[0.9956492,0.00009040397,0.001618282,0.0001224139,0.001998895,0.0005207847],"domain_scores_gemma":[0.9960449,0.00018144,0.0005188452,0.0006202477,0.0007893328,0.001845238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008554662,0.0002358238,0.09335133,0.002405371,0.000189816,0.00002689168,0.110641,0.00006968983,0.00002863913,0.002570993,0.1229436,0.6666814],"study_design_scores_gemma":[0.004941738,0.007166388,0.01118366,0.0004817957,0.00003712401,0.0007132434,0.09057973,0.001077555,0.0004658182,0.00004030234,0.88293,0.0003826615],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4099565,0.00004388661,0.1517203,0.4315506,0.0008540137,0.004251763,0.0005468195,0.0002880921,0.000788127],"genre_scores_gemma":[0.4912118,0.0002306711,0.04359973,0.4615097,0.0003862889,0.0003762308,0.00240448,0.0000405347,0.0002405648],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7599864,"threshold_uncertainty_score":0.6191914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08578863891101715,"score_gpt":0.432874207899904,"score_spread":0.3470855689888869,"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."}}