{"id":"W3111853578","doi":"10.2196/24445","title":"Telehealth Demand Trends During the COVID-19 Pandemic in the Top 50 Most Affected Countries: Infodemiological Evaluation","year":2020,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Telehealth; Pandemic; Coronavirus disease 2019 (COVID-19); Index (typography); Information and Communications Technology; Medicine; Business; Telemedicine; Demography; Geography; Health care; Economic growth; Computer science; Economics; Sociology; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.001415619,0.0003651593,0.0003667152,0.005852227,0.0002097093,0.001358651,0.0003942166,0.0004412965,0.002021768],"category_scores_gemma":[0.004722769,0.0001900634,0.0009744147,0.007650948,0.0003313838,0.001814633,0.0008800405,0.0004535046,0.000493873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008497556,"about_ca_system_score_gemma":0.000474337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01395344,"about_ca_topic_score_gemma":0.009911002,"domain_scores_codex":[0.9990632,0.0002290656,0.0001902977,0.0001473166,0.0002113792,0.0001587774],"domain_scores_gemma":[0.995977,0.001178831,0.001638085,0.00009303546,0.0008122133,0.0003008671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001571771,0.00005724016,0.9906764,0.0002200579,0.000115779,0.0001189,0.0003397413,0.001023991,0.0001212143,0.0001501244,0.001503997,0.00551529],"study_design_scores_gemma":[0.000006862972,0.0001646463,0.9924356,0.00006244009,0.00004899955,0.0001939236,0.002175713,0.003364178,0.0001876096,0.00006181836,0.001282104,0.00001606396],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9601017,0.0005686948,0.0002590791,0.0002672955,0.000011367,0.0001117999,0.03579574,0.00002776036,0.002856646],"genre_scores_gemma":[0.9781477,0.0004626921,0.0004016573,0.00006797435,0.00002712319,0.0001213756,0.02043268,0.000009399188,0.0003291704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01395344,"threshold_uncertainty_score":0.02774447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1115445262348445,"score_gpt":0.4180052339144816,"score_spread":0.3064607076796372,"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."}}