{"id":"W1971647508","doi":"10.1007/s13721-014-0051-4","title":"Efficient consumption of the electronic health record in mHealth","year":2014,"lang":"en","type":"article","venue":"Network Modeling Analysis in Health Informatics and Bioinformatics","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Middleware (distributed applications); mHealth; Mobile computing; Mobile device; Computer network; Health informatics; Mobile technology; Health care; Distributed computing; World Wide Web","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":[0.001241442,0.0005629639,0.0007107073,0.0007406891,0.0005721151,0.001927741,0.0009930714,0.0007348806,0.003089706],"category_scores_gemma":[0.00564626,0.0004087373,0.0005222301,0.001253041,0.0003521928,0.002896583,0.0009275392,0.0005074128,0.0005447948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124673,"about_ca_system_score_gemma":0.001468103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009293644,"about_ca_topic_score_gemma":0.008903651,"domain_scores_codex":[0.9987844,0.0005260345,0.00007056013,0.0001700244,0.000309618,0.0001394123],"domain_scores_gemma":[0.9980059,0.00110491,0.0001331824,0.000395284,0.0003086397,0.00005211818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001348877,0.0006142637,0.02273845,0.0002602241,0.0002334416,0.0003662941,0.0004279684,0.5516156,0.01876919,0.03643314,0.006038748,0.3611539],"study_design_scores_gemma":[0.000009022182,0.00004012095,0.001920251,0.00001062791,0.00003884412,0.0000468449,0.0001002374,0.9863126,0.004867175,0.005734105,0.0009121694,0.000008095164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3165061,0.000785323,0.6692976,0.00179212,0.0000932482,0.0001625986,0.0009018522,0.001562482,0.008898752],"genre_scores_gemma":[0.9463807,0.0002631127,0.04993973,0.00007700369,0.00002386557,0.00004345136,0.0003963676,0.0000942042,0.002781484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009293644,"threshold_uncertainty_score":0.01847911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02255559876076237,"score_gpt":0.2755305174859618,"score_spread":0.2529749187251994,"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."}}