{"id":"W2607303733","doi":"10.2196/jmir.5604","title":"Who Uses Mobile Phone Health Apps and Does Use Matter? A Secondary Data Analytics Approach","year":2017,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":599,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"","keywords":"Internet privacy; Mobile phone; Mobile apps; Analytics; mHealth; Phone; Usage data; Computer science; World Wide Web; eHealth; Data science; Health care; Medicine; Psychological intervention; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01500235,0.0007868437,0.001846487,0.007810991,0.001324396,0.002372907,0.001459829,0.001588375,0.006613842],"category_scores_gemma":[0.0475751,0.0005947477,0.003490266,0.01063937,0.001078181,0.00248929,0.002722137,0.002093886,0.002057937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001763121,"about_ca_system_score_gemma":0.004103724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01371191,"about_ca_topic_score_gemma":0.007928221,"domain_scores_codex":[0.9879705,0.004827093,0.00189287,0.002231734,0.001929012,0.001148746],"domain_scores_gemma":[0.9620813,0.02453437,0.005162764,0.002350203,0.004668031,0.00120334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000859718,0.0011914,0.9338033,0.002313722,0.001389975,0.0002852436,0.008412039,0.0008745759,0.0003224668,0.003017431,0.01363309,0.033897],"study_design_scores_gemma":[0.0003332357,0.001675,0.9216616,0.002152615,0.001603662,0.0004623428,0.02513137,0.01317916,0.0008233844,0.005973394,0.02684926,0.0001549551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8523582,0.0020402,0.02097823,0.003767818,0.0002615451,0.01354088,0.09259348,0.0002923532,0.01416739],"genre_scores_gemma":[0.9248575,0.0008207769,0.01546395,0.001585004,0.0001794102,0.0272639,0.02693202,0.0001121394,0.002785421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01500235,"threshold_uncertainty_score":0.07934099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3228889416664136,"score_gpt":0.5764566333492122,"score_spread":0.2535676916827985,"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."}}