{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002402174,0.0001513572,0.0003302677,0.0009614159,0.00009758887,0.00002142431,0.00007168461,0.00009002133,0.00002937783],"category_scores_gemma":[0.002702324,0.0001404534,0.00001934289,0.001474714,0.00003111634,0.0001328638,0.000142786,0.0002921489,0.00004407837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006518463,"about_ca_system_score_gemma":0.0005327811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002599859,"about_ca_topic_score_gemma":0.0005855102,"domain_scores_codex":[0.9981631,0.00003409883,0.0004836698,0.0003984788,0.0003077003,0.0006129685],"domain_scores_gemma":[0.99887,0.0002442475,0.00009748104,0.0001077808,0.00004984572,0.0006306584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006452774,0.0001222374,0.7605664,0.001986118,0.00001120827,0.0003906634,0.01694852,0.000004792097,0.1098885,0.0001446579,0.01763201,0.08585221],"study_design_scores_gemma":[0.008043251,0.001395052,0.9118953,0.0002789376,0.00002363098,0.000119841,0.007144916,0.0005270301,0.003270798,0.0004874465,0.06651469,0.0002990708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9577841,0.00002937037,0.00007870449,0.04080606,0.00006248246,0.0008953619,0.00001480364,0.0002010796,0.0001280364],"genre_scores_gemma":[0.9883059,0.00006398839,0.0005260703,0.01070161,0.0001147744,0.0001095198,0.00001386143,0.00002979526,0.0001345002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.151329,"threshold_uncertainty_score":0.5727522,"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."}}