{"id":"W2070952583","doi":"10.1109/jbhi.2014.2301156","title":"Development of mHealth Applications for Pre-Eclampsia Triage","year":2014,"lang":"en","type":"article","venue":"IEEE Journal of Biomedical and Health Informatics","topic":"Neonatal Respiratory Health Research","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of British Columbia; Grand Challenges Canada; Bill and Melinda Gates Foundation","keywords":"mHealth; Triage; Medicine; Medical emergency; Eclampsia; Mobile phone; Telemedicine; Referral; Health care; Computer science; Pregnancy; Family medicine; Nursing; Telecommunications; Psychological intervention","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002525528,0.0007696464,0.0004828088,0.0009529037,0.0004356659,0.001529488,0.001225227,0.0009057239,0.00358325],"category_scores_gemma":[0.006335483,0.00037356,0.0005728337,0.0004108535,0.000198434,0.001457106,0.0008472323,0.001077048,0.002444931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003202308,"about_ca_system_score_gemma":0.0009890415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009452114,"about_ca_topic_score_gemma":0.0009504003,"domain_scores_codex":[0.9988301,0.0002235947,0.0001458871,0.0001249713,0.0005732536,0.0001022292],"domain_scores_gemma":[0.9963206,0.001237111,0.0001591645,0.0002220533,0.001812681,0.0002483608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009268008,0.000877818,0.007475791,0.001463549,0.00009698346,0.002087303,0.001138468,0.002230982,0.06982099,0.002354777,0.02653611,0.8849904],"study_design_scores_gemma":[0.0009590636,0.006604935,0.05016415,0.002425792,0.0005610247,0.006032602,0.001995737,0.1138112,0.3124429,0.006246534,0.4982495,0.0005065005],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1742393,0.00424719,0.6993278,0.003366904,0.00237941,0.0140867,0.004000925,0.06919798,0.02915381],"genre_scores_gemma":[0.1999879,0.002577989,0.763742,0.001518164,0.0003371151,0.003598263,0.004446315,0.001504725,0.02228764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00358325,"threshold_uncertainty_score":0.01335639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09951777413278212,"score_gpt":0.4520898469881459,"score_spread":0.3525720728553637,"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."}}