{"id":"W4205687123","doi":"10.20517/ch.2021.03","title":"The worldwide impact of telemedicine during COVID-19: current evidence and recommendations for the future","year":2022,"lang":"en","type":"article","venue":"Connected Health","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":373,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint John Regional Hospital; University of Toronto; University of British Columbia; Lunenfeld-Tanenbaum Research Institute; University of Alberta","funders":"National Center for Advancing Translational Sciences; National Heart, Lung, and Blood Institute; National Institute for Health and Care Research","keywords":"Telemedicine; Reimbursement; Health care; License; Business; Pandemic; Population; Coronavirus disease 2019 (COVID-19); Medical emergency; Medicine; Disease; Computer science; Environmental health; Economic growth","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001705382,0.0001213653,0.0002727559,0.0001191209,0.002026752,0.000008905698,0.0001257216,0.00001576546,0.000316345],"category_scores_gemma":[0.001250567,0.00006765826,0.00007246327,0.0004755464,0.00008687671,0.00004681508,0.00007091774,0.0003635259,3.755238e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005074777,"about_ca_system_score_gemma":0.001662503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007288391,"about_ca_topic_score_gemma":0.0005140417,"domain_scores_codex":[0.9983075,0.0002221655,0.0005983745,0.000214106,0.000283064,0.0003747345],"domain_scores_gemma":[0.9966703,0.002114214,0.0004105448,0.0003206581,0.000128921,0.0003553448],"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":[0.001913085,0.000192871,0.1274742,0.001939862,0.0001750513,0.000003522512,0.008401202,0.00004014053,0.0002041723,0.002895645,0.3492279,0.5075323],"study_design_scores_gemma":[0.005078376,0.002894518,0.4515209,0.000166292,0.0001216384,0.0001387561,0.01283094,0.0005787609,0.00001625329,0.0003968631,0.5261486,0.0001081466],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3080941,0.0426677,0.001214948,0.6432655,0.0008537201,0.003653727,0.0001768625,0.00006695021,0.000006416525],"genre_scores_gemma":[0.9786371,0.01251207,0.0001957254,0.007184979,0.0006644223,0.0005534145,0.0001722452,0.00001927652,0.00006073728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.670543,"threshold_uncertainty_score":0.9992725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08823889946950593,"score_gpt":0.4635277340285049,"score_spread":0.375288834558999,"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."}}