{"id":"W2809354366","doi":"10.2196/mhealth.9345","title":"Mobile Apps for Caregivers of Older Adults: Quantitative Content Analysis","year":2018,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":141,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging","keywords":"Psychological intervention; mHealth; Caregiver burden; Family caregivers; Intervention (counseling); Social support; Psychology; Mobile apps; Internet privacy; Applied psychology; Nursing; Medicine; Computer science; World Wide Web; Social psychology; Dementia","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001609643,0.0003137439,0.001046235,0.0005713025,0.00172045,0.000006340206,0.0002399478,0.0003501186,0.0002423923],"category_scores_gemma":[0.0001806642,0.0002800066,0.0001877029,0.001236222,0.0003771585,0.0001185603,0.00007192706,0.0005015562,0.00006005269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002758549,"about_ca_system_score_gemma":0.001738909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002565088,"about_ca_topic_score_gemma":0.001909134,"domain_scores_codex":[0.9952002,0.000449519,0.001775973,0.0007965423,0.0003324221,0.001445377],"domain_scores_gemma":[0.9943967,0.001071445,0.001275239,0.0006639706,0.001251941,0.001340732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01247197,0.001975998,0.2180447,0.06522281,0.0009037667,0.000002564734,0.1517448,0.00001384783,0.00009261489,0.1977717,0.1014427,0.2503125],"study_design_scores_gemma":[0.01894136,0.01025485,0.4245287,0.001629586,0.001929728,0.000004381153,0.11684,0.00525044,0.00006174111,0.00181374,0.4176267,0.00111886],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9546096,0.005707162,0.01210479,0.002148889,0.0009033413,0.02035571,0.001225113,0.0002178325,0.002727561],"genre_scores_gemma":[0.9660482,0.003588731,0.005727311,0.003516825,0.0003699107,0.01971298,0.0002695321,0.00004991311,0.0007165425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.316184,"threshold_uncertainty_score":0.9999652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1146885030173616,"score_gpt":0.482736814144354,"score_spread":0.3680483111269925,"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."}}