{"id":"W2401346024","doi":"10.5588/pha.15.0074","title":"Connecting patient care to global health trends by health app analytics","year":2015,"lang":"en","type":"article","venue":"Public Health Action","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Analytics; mHealth; Android (operating system); Internet privacy; Health care; Mobile phone; Medicine; World Wide Web; Computer science; Data science; Nursing; Psychological intervention; Telecommunications","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":[0.00749116,0.001578429,0.0008837845,0.01576828,0.0008610919,0.009991571,0.001765727,0.00222085,0.01323384],"category_scores_gemma":[0.04763266,0.0006394726,0.001745174,0.01683464,0.00128475,0.01212089,0.007012971,0.00372878,0.007614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001774031,"about_ca_system_score_gemma":0.002263371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007552329,"about_ca_topic_score_gemma":0.009596867,"domain_scores_codex":[0.9944911,0.002022596,0.0007633059,0.0009623144,0.001446727,0.0003139664],"domain_scores_gemma":[0.9752956,0.0138888,0.003572383,0.002675196,0.003427225,0.001140886],"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":[0.0001378745,0.0001316934,0.07371,0.002069506,0.0004136384,0.000202703,0.003494059,0.002138678,0.0003853709,0.02351961,0.3305253,0.5632717],"study_design_scores_gemma":[0.00008503416,0.0001906733,0.05452209,0.00572248,0.000310137,0.0005013631,0.008718421,0.0219865,0.001467132,0.1200359,0.7861781,0.0002820458],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06042622,0.07242506,0.143313,0.3480015,0.02074272,0.002657629,0.1096246,0.0261422,0.216667],"genre_scores_gemma":[0.447727,0.08029445,0.2742176,0.05730693,0.02797885,0.002491214,0.08848828,0.003969882,0.01752578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01576828,"threshold_uncertainty_score":0.04427159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1817115920332441,"score_gpt":0.5160131518604615,"score_spread":0.3343015598272174,"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."}}