{"id":"W2904214837","doi":"10.2196/10925","title":"Crossing the Digital Divide in Online Self-Management Support: Analysis of Usage Data From HeLP-Diabetes","year":2018,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute for Health and Care Research","keywords":"Digital divide; Psychological intervention; The Internet; Digital health; Socioeconomic status; Internet privacy; Ethnic group; Gerontology; Affect (linguistics); Health care; Psychology; Medicine; Computer science; Nursing; Environmental health; World Wide Web; Political science; Population","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":[0.001049743,0.0002174226,0.0005746934,0.0003718962,0.0008649775,0.00006098993,0.0009989141,0.0001582444,0.0007561917],"category_scores_gemma":[0.0001687275,0.0001631417,0.00009034088,0.001649285,0.000280163,0.0002922605,0.0007782074,0.0004195599,0.0002457419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000109874,"about_ca_system_score_gemma":0.000317356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002008921,"about_ca_topic_score_gemma":0.001622958,"domain_scores_codex":[0.9965857,0.0002632032,0.001191611,0.0006244226,0.0003475392,0.000987567],"domain_scores_gemma":[0.995692,0.001456291,0.0005377649,0.001930103,0.0001305241,0.0002533126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001095312,0.0003486136,0.9591658,0.0003217824,0.0003048135,5.442891e-7,0.001099156,0.000004343523,0.00005971428,0.0001875144,0.01339953,0.02509725],"study_design_scores_gemma":[0.0005741681,0.00005697016,0.7712343,0.0001529784,0.0003030878,8.406039e-9,0.0006513373,0.005341224,0.00002558801,0.0004393927,0.2210725,0.0001485336],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889237,0.0002839545,0.00004888508,0.001939109,0.0002218736,0.002561869,0.003676228,0.0001180356,0.002226296],"genre_scores_gemma":[0.9901873,0.00008810145,0.0006826335,0.002755023,0.0004825924,0.002060164,0.003360641,0.00003071421,0.0003527968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2076729,"threshold_uncertainty_score":0.8279768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05794444376684319,"score_gpt":0.4244933604016763,"score_spread":0.3665489166348331,"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."}}