{"id":"W3092596287","doi":"10.2196/23176","title":"Disparities in Video and Telephone Visits Among Older Adults During the COVID-19 Pandemic: Cross-Sectional Analysis","year":2020,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Research Resources; Centers for Medicare and Medicaid Services; National Institute on Aging; National Institutes of Health","keywords":"Medicine; Telemedicine; Pandemic; Medical diagnosis; Reimbursement; Telehealth; Cross-sectional study; Coronavirus disease 2019 (COVID-19); Videoconferencing; Health care; Medical emergency; Family medicine; Disease; Multimedia","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":[0.001380231,0.0001699521,0.0003155515,0.001271266,0.0003490663,0.0004700797,0.0003224599,0.0005132393,0.001147773],"category_scores_gemma":[0.00363736,0.0002462859,0.0005022345,0.001563638,0.0002137448,0.0006144983,0.0006004846,0.0004113314,0.0001213657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000393295,"about_ca_system_score_gemma":0.0003671308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01141041,"about_ca_topic_score_gemma":0.0147245,"domain_scores_codex":[0.9990863,0.0002450208,0.0001491985,0.0001939364,0.0001791446,0.0001464566],"domain_scores_gemma":[0.996707,0.0007881334,0.00170357,0.0001503288,0.0002778234,0.0003731477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003369385,0.00003026263,0.9993286,0.000007300091,0.0000263086,0.00001210889,0.0001107324,0.00001029436,0.00004499221,0.000005999671,0.00003879418,0.0003509114],"study_design_scores_gemma":[0.000002869838,0.00007044273,0.9994493,0.000005227467,0.00001265138,0.00004005828,0.0002967076,0.00006605244,0.0000137126,0.000003178439,0.00003826506,0.000001596651],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999249,0.00008823792,0.00003240172,0.00001921392,0.000002029989,0.00001315035,0.0004590136,0.000001081065,0.0001357893],"genre_scores_gemma":[0.999398,0.00006641191,0.00006304818,0.00002914358,0.000006101274,0.00002118664,0.0003767306,8.794415e-7,0.00003855617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01141041,"threshold_uncertainty_score":0.02268797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03479286358307308,"score_gpt":0.3713995025145994,"score_spread":0.3366066389315263,"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."}}