{"id":"W3037691155","doi":"10.2196/19661","title":"Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study","year":2020,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":216,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"eHealth; Health literacy; Medicine; Family medicine; Medical education; Health care; 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":[0.001694362,0.0001980334,0.0004681582,0.0007933231,0.0005188803,0.0007072931,0.0002779162,0.000660247,0.002044418],"category_scores_gemma":[0.003837093,0.000347035,0.0006891786,0.001738239,0.0003028977,0.001010511,0.0007686133,0.000772146,0.0006101665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006048837,"about_ca_system_score_gemma":0.0006232531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005074059,"about_ca_topic_score_gemma":0.006768408,"domain_scores_codex":[0.9985787,0.0004973342,0.0002749942,0.0001831493,0.0002253376,0.0002404712],"domain_scores_gemma":[0.9973062,0.0005241369,0.001295396,0.000114434,0.0003313851,0.0004284129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008417256,0.0002166131,0.9959032,0.00007656658,0.00004439798,0.0000950542,0.001113324,0.00002212346,0.0001035884,0.00001379776,0.0002825642,0.00204451],"study_design_scores_gemma":[0.00002956711,0.0004455111,0.9961169,0.00003877693,0.00003649759,0.0004103037,0.002190059,0.0001260901,0.00005555111,0.00001240758,0.0005253545,0.00001301434],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983432,0.000123576,0.00006942724,0.00008813875,0.000002216264,0.00007487598,0.0009607007,0.000002672854,0.0003349725],"genre_scores_gemma":[0.9987531,0.0001604595,0.0001670769,0.0001540542,0.000006154226,0.0001276453,0.0004931704,0.000001831186,0.0001366106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005074059,"threshold_uncertainty_score":0.01008904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09156484980033913,"score_gpt":0.4644070392663942,"score_spread":0.372842189466055,"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."}}