{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01801312,0.0001822982,0.0007563006,0.0003982244,0.001521468,0.0001955,0.002915713,0.0004095452,0.002748526],"category_scores_gemma":[0.00425442,0.0001168927,0.00006353703,0.0001699107,0.0007595771,0.0006309003,0.002237506,0.005355364,0.0001743356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002604901,"about_ca_system_score_gemma":0.004963687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004834632,"about_ca_topic_score_gemma":0.00121115,"domain_scores_codex":[0.9925105,0.001711182,0.001763962,0.0004990865,0.002337677,0.00117758],"domain_scores_gemma":[0.9914598,0.002218819,0.001212559,0.001847749,0.0007495064,0.002511512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002705131,0.0003553107,0.06245315,0.001985896,0.000075318,0.00004318869,0.001142328,4.228066e-7,0.00000470122,0.001240929,0.8439204,0.08850788],"study_design_scores_gemma":[0.00232558,0.0005034336,0.07020947,0.001895257,0.0000195473,0.0001374776,0.002806755,0.004754497,0.000004529057,0.0006541247,0.916536,0.0001532876],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.679379,0.01304051,0.01499575,0.2676684,0.00326233,0.008819137,0.0007674646,0.00008463406,0.01198277],"genre_scores_gemma":[0.9085345,0.05002423,0.004518487,0.01482665,0.004281164,0.001092925,0.0001443982,0.0001130804,0.01646459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2528418,"threshold_uncertainty_score":0.9997784,"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."}}