{"id":"W4206307666","doi":"10.2196/preprints.23914","title":"Prescribing Phones to Address Health Equity Needs in the COVID-19 Era: The PHONE-CONNECT Program (Preprint)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McKnight Foundation","keywords":"Phone; Health care; Public health; Digital health; Poverty; Intervention (counseling); Internet privacy; Social media; Telemedicine; Health equity; Medicine; Business; Public relations; Nursing; Political science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002895565,0.0001770727,0.0002371367,0.0002975624,0.001253867,0.001770624,0.0006298654,0.001014433,0.02782491],"category_scores_gemma":[0.01741518,0.0001357034,0.0003248844,0.000605256,0.0004105169,0.001073992,0.001163381,0.001529249,0.001893101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002585907,"about_ca_system_score_gemma":0.008958337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06459595,"about_ca_topic_score_gemma":0.1315026,"domain_scores_codex":[0.9985167,0.0008682036,0.00005194889,0.00006167107,0.0002882305,0.0002133167],"domain_scores_gemma":[0.9932834,0.003350945,0.0004790849,0.0001973305,0.0008771661,0.001812048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001962199,0.005166509,0.04780475,0.002068101,0.0001249037,0.0001796435,0.006111206,0.0001616296,0.0004418536,0.004983945,0.6175176,0.3134777],"study_design_scores_gemma":[0.004246161,0.00837521,0.5350429,0.006098322,0.000654911,0.0001726263,0.02832568,0.000532478,0.00192001,0.002399985,0.4121655,0.00006626622],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.4991961,0.007176847,0.0007503657,0.2687002,0.006580439,0.004267674,0.0163784,0.0002811838,0.1966687],"genre_scores_gemma":[0.8103595,0.01461441,0.00494178,0.07703382,0.004466678,0.007231794,0.008079406,0.0002086323,0.07306384],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.06459595,"threshold_uncertainty_score":0.1284399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1456471469996431,"score_gpt":0.42347500578301,"score_spread":0.2778278587833669,"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."}}