{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.004926633,0.0004941513,0.001111909,0.0005437761,0.003840676,0.00006302876,0.0003897175,0.000356093,0.0001884898],"category_scores_gemma":[0.000835676,0.0005118056,0.000123506,0.002815153,0.00003816326,0.0003791762,0.0001885114,0.001290674,0.0006200087],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01696687,"about_ca_system_score_gemma":0.02328479,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02019026,"about_ca_topic_score_gemma":0.01468739,"domain_scores_codex":[0.9887765,0.002333072,0.002891022,0.001144855,0.001068281,0.003786247],"domain_scores_gemma":[0.9854504,0.0002590508,0.002063822,0.001034988,0.0009542244,0.01023748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004181046,0.0001466763,0.002265073,0.0007477778,0.000009608832,2.399101e-7,0.005664991,0.00003773048,3.305954e-7,0.001350766,0.3828424,0.6068926],"study_design_scores_gemma":[0.001423124,0.001784814,0.00389852,0.0001500161,0.000004210125,0.000009347427,0.02920586,0.0003483219,6.169252e-7,0.0001222113,0.9627602,0.0002927787],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02473097,0.01204247,0.05867902,0.8643907,0.008880048,0.01409836,0.002426573,0.002453787,0.01229806],"genre_scores_gemma":[0.7767528,0.001503955,0.005119357,0.2045681,0.00154849,0.006986696,0.002746292,0.0001470476,0.0006272979],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.7520218,"threshold_uncertainty_score":0.9997333,"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."}}