{"id":"W4206252914","doi":"10.2196/preprints.26960","title":"Rural Telemedicine Use Before and During the COVID-19 Pandemic: Repeated Cross-sectional Study (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Sinai Health System; University of Toronto; Women's College Hospital","funders":"Ontario Ministry of Health and Long-Term Care","keywords":"Telemedicine; Pandemic; Medicine; Coronavirus disease 2019 (COVID-19); Rural area; Cross-sectional study; Population; Rural population; Telehealth; Demography; Medical emergency; Health care; Environmental health; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007641219,0.0002053534,0.000239816,0.0005545766,0.0005272346,0.0005830939,0.0004984898,0.0005474983,0.001500933],"category_scores_gemma":[0.002440067,0.0004170275,0.0005826675,0.001239313,0.0002559889,0.0005428114,0.000481523,0.0005054686,0.0003553454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120039,"about_ca_system_score_gemma":0.001132614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1797399,"about_ca_topic_score_gemma":0.2357591,"domain_scores_codex":[0.999278,0.0001601013,0.00008702908,0.000171144,0.0001632239,0.0001404938],"domain_scores_gemma":[0.997497,0.0002990295,0.001258403,0.0001651692,0.0004056974,0.0003746556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004439185,0.0000349417,0.9989379,0.00001208403,0.00003331623,0.00001991981,0.00016697,0.00001092562,0.00007566281,0.000004245916,0.0002176986,0.0004419109],"study_design_scores_gemma":[0.000005020991,0.00007007358,0.9994701,0.000005537267,0.00001148393,0.00003262814,0.0002156996,0.00003971505,0.00001921115,0.000001830542,0.0001264158,0.000002414929],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968429,0.0001023012,0.00006925331,0.00007337664,0.000007369099,0.00003453944,0.00242814,0.000005576429,0.0004366165],"genre_scores_gemma":[0.9978377,0.00009152027,0.0001104776,0.0001200545,0.00001558211,0.00005409221,0.001441212,0.000003464978,0.0003258105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1797399,"threshold_uncertainty_score":0.3573874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08051267622572363,"score_gpt":0.4099542719132112,"score_spread":0.3294415956874876,"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."}}