{"id":"W4211242189","doi":"10.2196/35221","title":"Socioeconomic Disparities in the Demand for and Use of Virtual Visits Among Senior Adults During the COVID-19 Pandemic: Cross-sectional Study","year":2022,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Health Infoway","funders":"Government of Canada","keywords":"Socioeconomic status; Pandemic; Cross-sectional study; Health care; Medicine; Logistic regression; Gerontology; Social distance; Population; Environmental health; Coronavirus disease 2019 (COVID-19); Demography; Disease; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009263976,0.00007979235,0.0001515536,0.00009023127,0.0004769341,0.00003078442,0.00006710376,0.00001751598,0.00005026496],"category_scores_gemma":[0.0000849404,0.00005398993,0.00003360882,0.00006864619,0.00006808423,0.0001162102,0.00006633007,0.0001983232,1.879994e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000138091,"about_ca_system_score_gemma":0.00006684279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001158435,"about_ca_topic_score_gemma":0.0008498523,"domain_scores_codex":[0.9989876,0.000118854,0.0003557866,0.000176776,0.000186637,0.0001744118],"domain_scores_gemma":[0.9990152,0.0006607586,0.0001354608,0.0001174183,0.00002238497,0.00004875156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003267345,0.00007317595,0.9868256,0.0001481901,0.00002440185,0.000005038811,0.01180825,0.0001065982,0.00003620692,0.00002913815,0.0002066303,0.0004100704],"study_design_scores_gemma":[0.004415642,0.0003522155,0.9791251,0.000008109491,0.00002006813,0.0000641041,0.01503805,0.0003294329,0.000006061108,0.00002996662,0.0005602641,0.00005092824],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969894,0.00004546999,0.0000653146,0.0009062391,0.00007206568,0.001853579,0.00004717138,0.00001828587,0.000002492597],"genre_scores_gemma":[0.9975274,0.00000800428,0.00001372651,0.001510299,0.0001234181,0.0007010268,0.00003159409,0.00001014931,0.00007443545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007700399,"threshold_uncertainty_score":0.366824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05135072229537238,"score_gpt":0.3879877327246633,"score_spread":0.336637010429291,"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."}}