{"id":"W4382456640","doi":"10.2196/41686","title":"Improving Telehealth Equity in Response to COVID-19 in California: ACTIVATE and Lighthouse","year":2023,"lang":"en","type":"article","venue":"Iproceedings","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Telehealth; Health care; Telemedicine; Equity (law); Health equity; Digital health; Health literacy; Business; Nursing; Medicine; Public health; Political science","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":[0.004525119,0.0002848858,0.0001677828,0.0005464098,0.003137987,0.003159205,0.001530856,0.001652698,0.005061122],"category_scores_gemma":[0.007598564,0.0002841642,0.0004007419,0.0005210884,0.001595391,0.002382006,0.003567889,0.003275119,0.0002366725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00727281,"about_ca_system_score_gemma":0.03082241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.104184,"about_ca_topic_score_gemma":0.2285672,"domain_scores_codex":[0.9975873,0.0008151847,0.00006858912,0.0002274332,0.0005440767,0.0007573933],"domain_scores_gemma":[0.993391,0.001851294,0.0003449989,0.0002264181,0.0008591623,0.003327184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000397913,0.005147943,0.1036512,0.00119426,0.000101113,0.0007915523,0.01761041,0.001702021,0.001594081,0.01187089,0.1999954,0.6559432],"study_design_scores_gemma":[0.001531993,0.004762803,0.4538311,0.004232908,0.0003402191,0.000609039,0.1032417,0.00463065,0.002758704,0.006983966,0.4168303,0.0002466449],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.671604,0.005386796,0.004555603,0.2276055,0.001363045,0.0021776,0.0008078357,0.000453479,0.08604614],"genre_scores_gemma":[0.9292498,0.005978952,0.01385719,0.03094964,0.0005883274,0.001778018,0.0008015794,0.00008629057,0.01671026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.104184,"threshold_uncertainty_score":0.2071551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07162677945827664,"score_gpt":0.4277950899119754,"score_spread":0.3561683104536988,"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."}}