{"id":"W4387564167","doi":"10.2196/46654","title":"An Evidence-Based Framework for Creating Inclusive and Personalized mHealth Solutions—Designing a Solution for Medicaid-Eligible Pregnant Individuals With Uncontrolled Type 2 Diabetes","year":2023,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Healthcare Research and Quality; Ohio State University","keywords":"mHealth; Personalization; Medicaid; Personalized medicine; Medicine; Type 2 diabetes; Internet privacy; Psychology; Computer science; Health care; Nursing; Diabetes mellitus; World Wide Web; Bioinformatics; Psychological intervention","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":[0.117037,0.003986785,0.00238283,0.01674415,0.007445307,0.01776019,0.009848354,0.01475775,0.006831512],"category_scores_gemma":[0.103194,0.001967578,0.004952279,0.005225757,0.01591612,0.01094541,0.01745394,0.01220321,0.002899763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01334681,"about_ca_system_score_gemma":0.07269033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01064327,"about_ca_topic_score_gemma":0.01996344,"domain_scores_codex":[0.8770741,0.09090258,0.0129056,0.004184763,0.01210714,0.002825825],"domain_scores_gemma":[0.9089955,0.06082891,0.005481319,0.004230734,0.01542068,0.005042794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000208101,0.001166369,0.004568347,0.02254121,0.0004914179,0.001215962,0.01419604,0.006901594,0.001387289,0.6050352,0.02645923,0.3158292],"study_design_scores_gemma":[0.000539933,0.001016048,0.002954745,0.09810252,0.00128723,0.001080721,0.01713042,0.009449109,0.003397319,0.4775659,0.3871765,0.0002996261],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009365311,0.03494102,0.4600922,0.3281816,0.002540314,0.01932449,0.001139538,0.0008131858,0.1436023],"genre_scores_gemma":[0.06881689,0.01375165,0.8892519,0.01384735,0.0002870307,0.01002504,0.0004824873,0.0000873382,0.003450341],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.117037,"threshold_uncertainty_score":0.6189582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08155376333728478,"score_gpt":0.443733761116898,"score_spread":0.3621799977796132,"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."}}