{"id":"W3166858036","doi":"10.2196/28964","title":"An innovative mobile application for gestational diabetes health education during the COVID-19 pandemic (Preprint)","year":2021,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chinese Academy of Medical Sciences","keywords":"Gestational diabetes; Pandemic; Preprint; The Internet; Medicine; Pregnancy; Promotion (chess); Coronavirus disease 2019 (COVID-19); Telemedicine; Mobile apps; Medical education; Obstetrics; Health care; Computer science; Political science; Internal medicine; Gestation; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0005731332,0.0008420576,0.0003196881,0.0006601709,0.0004247791,0.0008001339,0.0005896697,0.001442502,0.02402858],"category_scores_gemma":[0.00259822,0.0001635592,0.0005770667,0.0002257616,0.0001433104,0.0008121777,0.001365022,0.0006948728,0.007381933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001482419,"about_ca_system_score_gemma":0.0003953439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004698961,"about_ca_topic_score_gemma":0.0008476389,"domain_scores_codex":[0.9996824,0.0001144503,0.00003097848,0.00004407918,0.00007406044,0.00005405558],"domain_scores_gemma":[0.9989039,0.0006842957,0.00005522397,0.00004387422,0.0001359779,0.0001767544],"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":[0.001098906,0.001060318,0.006736521,0.001677414,0.00006914817,0.002113322,0.00143886,0.0003889251,0.01349118,0.001330187,0.2034765,0.7671187],"study_design_scores_gemma":[0.001439745,0.004060328,0.04963285,0.002751935,0.0006317293,0.01063833,0.00239791,0.01356041,0.01629508,0.005694715,0.8924352,0.0004617503],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2545768,0.01787624,0.3090199,0.01957587,0.009824383,0.009009613,0.01697208,0.2032015,0.1599436],"genre_scores_gemma":[0.4815902,0.009221384,0.3311928,0.01643581,0.002810478,0.005719163,0.009853577,0.003451761,0.1397247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02402858,"threshold_uncertainty_score":0.0803836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02721822341112202,"score_gpt":0.3923686001678218,"score_spread":0.3651503767566998,"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."}}