{"id":"W2966881924","doi":"10.11124/jbisrir-d-19-00243","title":"Mobile health at critical moments: how bold is global health?","year":2019,"lang":"en","type":"letter","venue":"The JBI Database of Systematic Reviews and Implementation Reports","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"mHealth; Mobile technology; Short Message Service; eHealth; Internet privacy; Mobile phone; Business; Health care; Digital health; Telemedicine; Telecommunications; Computer science; Mobile computing; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01471342,0.001090559,0.002543168,0.002544737,0.003941582,0.0144919,0.002444527,0.0130259,0.01861751],"category_scores_gemma":[0.05380021,0.0006010956,0.001307225,0.003038261,0.009081488,0.0276822,0.007222728,0.01715311,0.004046845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005605782,"about_ca_system_score_gemma":0.01504252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007182891,"about_ca_topic_score_gemma":0.01169578,"domain_scores_codex":[0.9857297,0.008158253,0.0008023724,0.00114043,0.0026994,0.001469871],"domain_scores_gemma":[0.9498645,0.03094009,0.003053755,0.001228547,0.00625519,0.008657885],"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":[0.0001632489,0.00006862122,0.001938016,0.01210657,0.0002176145,0.0004885579,0.005130006,0.0001652695,0.000213581,0.04188934,0.5792628,0.3583565],"study_design_scores_gemma":[0.00004464727,0.0001613475,0.002103801,0.03542475,0.0001401647,0.0006094833,0.01021347,0.0001212843,0.0001177941,0.06081614,0.8901505,0.00009651973],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0004806779,0.1509576,0.0003815416,0.8360371,0.009488924,0.00001538723,0.00009471227,0.00003738825,0.002506699],"genre_scores_gemma":[0.0356824,0.4812653,0.002365801,0.4432158,0.03352299,0.0001198066,0.0002786238,0.0001333217,0.003415993],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01861751,"threshold_uncertainty_score":0.07781297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1117309719116565,"score_gpt":0.5169238139391883,"score_spread":0.4051928420275318,"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."}}