{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00435753,0.0002490199,0.0005397592,0.0051371,0.0005098507,0.001541275,0.000614548,0.0006792011,0.001644879],"category_scores_gemma":[0.01422545,0.0003359367,0.0008849242,0.007886266,0.0006005341,0.001106097,0.001778906,0.000582262,0.0005433264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001308131,"about_ca_system_score_gemma":0.001035519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01439598,"about_ca_topic_score_gemma":0.01765615,"domain_scores_codex":[0.9944927,0.002351542,0.001161703,0.0004358136,0.001118756,0.0004395148],"domain_scores_gemma":[0.9737431,0.01143112,0.01000749,0.0009724206,0.002846007,0.0009997735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001931277,0.00009943893,0.9936141,0.0001169529,0.00006906074,0.00007130695,0.001747064,0.00004582301,0.00007469712,0.00002355341,0.000179501,0.00376536],"study_design_scores_gemma":[0.00001136111,0.0001898301,0.9961117,0.000050189,0.00003748197,0.0001605653,0.002615392,0.0002151406,0.00008542494,0.000009362702,0.0005044289,0.000009132829],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974221,0.0001949779,0.00008613679,0.0000309793,0.00000190978,0.00007818244,0.001777605,0.000002839835,0.0004052727],"genre_scores_gemma":[0.9964301,0.0002267231,0.0002639643,0.00004578219,0.000007160788,0.0002533296,0.002467497,0.000005863116,0.0002996541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01439598,"threshold_uncertainty_score":0.02862436,"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."}}