{"id":"W2224587774","doi":"10.3978/j.issn.2306-9740.2015.03.10","title":"Leveraging standards-based, interoperable meHealth for universal health coverage.","year":2015,"lang":"en","type":"article","venue":"PubMed","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Activation Laboratories","funders":"","keywords":"mHealth; eHealth; Interoperability; Information and Communications Technology; Mobile phone; Internet privacy; Business; Telemedicine; Health informatics; Digital health; Health care; Computer science; Knowledge management; World Wide Web; Telecommunications; Political science","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":[0.01846907,0.0003498673,0.0004880792,0.005760738,0.0009395947,0.003214219,0.001647921,0.002015592,0.01234941],"category_scores_gemma":[0.04806693,0.000252306,0.001140653,0.003557905,0.001017569,0.005352717,0.005855002,0.002571609,0.004851578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002123913,"about_ca_system_score_gemma":0.01248197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006919057,"about_ca_topic_score_gemma":0.01056927,"domain_scores_codex":[0.989835,0.003621226,0.001910479,0.0004756053,0.003684182,0.0004733898],"domain_scores_gemma":[0.9715423,0.01219149,0.002320186,0.002852188,0.008757632,0.002336309],"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":[0.0000682568,0.0001029166,0.003206221,0.003590018,0.00007483036,0.0002570044,0.001051622,0.0002273966,0.001622636,0.03445777,0.161772,0.7935694],"study_design_scores_gemma":[0.00004968125,0.0001436922,0.008829098,0.006482074,0.00009001622,0.0005087583,0.0009425063,0.0005624909,0.001869321,0.02098311,0.9594999,0.00003937163],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01571789,0.1244996,0.1206484,0.3991323,0.01799305,0.003105535,0.01900849,0.003925592,0.2959691],"genre_scores_gemma":[0.2147817,0.1808118,0.4018714,0.1058945,0.01364357,0.003985086,0.03942102,0.0008884303,0.03870243],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01846907,"threshold_uncertainty_score":0.09767503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1263600306872288,"score_gpt":0.4178478377380693,"score_spread":0.2914878070508405,"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."}}