{"id":"W4395082423","doi":"10.2196/52317","title":"Adoption and Use of Telemedicine and Digital Health Services Among Older Adults in Light of the COVID-19 Pandemic: Repeated Cross-Sectional Analysis","year":2024,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Clalit Health Services","keywords":"Telehealth; Pandemic; Telemedicine; Telecare; Coronavirus disease 2019 (COVID-19); Population; Medicine; Family medicine; Health care; Gerontology; Environmental health; Political science; Disease","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000404172,0.00009917624,0.0002887847,0.0004121545,0.00005514018,0.00003008416,0.00003134172,0.0000477201,0.00002998706],"category_scores_gemma":[0.00005592625,0.00006729215,0.00004782042,0.0008492273,0.00009032676,0.0002404229,0.00003780451,0.0001523255,1.325138e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008427456,"about_ca_system_score_gemma":0.0001176477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002023124,"about_ca_topic_score_gemma":0.0009583075,"domain_scores_codex":[0.9986794,0.00004077849,0.0006018294,0.0002521332,0.0002674191,0.0001584665],"domain_scores_gemma":[0.9993095,0.0001453844,0.0002012539,0.0001395795,0.00006653505,0.0001377332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007324822,0.00003146658,0.9877045,0.002426823,0.00009009262,0.000005995695,0.003969936,0.00001414023,0.00009124264,0.00001299487,0.00007344544,0.005506143],"study_design_scores_gemma":[0.001471796,0.0001201574,0.9935095,0.0006492524,0.00008127523,0.00004735629,0.0009533009,0.002214295,0.00003048763,0.00001263888,0.0008624273,0.00004755666],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969586,0.0006545245,0.00016809,0.001502293,0.00005392303,0.0005722651,0.00003465326,0.00003799577,0.00001769102],"genre_scores_gemma":[0.9987022,0.0001583126,0.00005289311,0.0008026996,0.00006036028,0.00001955739,0.0001262479,0.000009309108,0.0000683769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005804986,"threshold_uncertainty_score":0.3058371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03096977403706011,"score_gpt":0.3777697716469725,"score_spread":0.3467999976099123,"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."}}