{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.004295775,0.0003549414,0.0007905249,0.0003906316,0.004631315,0.00004840835,0.0002723544,0.0004630798,0.0000529779],"category_scores_gemma":[0.003443668,0.0002913078,0.00009442354,0.0009756074,0.0002031823,0.0003409242,0.00008958099,0.0005394848,0.00002654627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003142429,"about_ca_system_score_gemma":0.002686085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006687923,"about_ca_topic_score_gemma":0.00007610242,"domain_scores_codex":[0.9950868,0.0006957179,0.000961534,0.0007928493,0.0004359442,0.002027165],"domain_scores_gemma":[0.9835771,0.01367596,0.0007624826,0.0004938993,0.0007016687,0.0007889341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002788157,0.0009321408,0.7136096,0.03173677,0.0005050917,0.000001546383,0.01757471,0.0004767781,0.008175097,0.07008003,0.04434786,0.1097722],"study_design_scores_gemma":[0.04778829,0.01895392,0.1223406,0.05909531,0.001645782,0.000001107279,0.01438012,0.4916428,0.001360235,0.1260994,0.1132298,0.003462625],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7585427,0.01516851,0.1043731,0.04647224,0.001043965,0.07112475,0.001058974,0.002075373,0.0001403761],"genre_scores_gemma":[0.7146755,0.0009882791,0.08400564,0.007041898,0.001103313,0.1909609,0.0008513546,0.0001607073,0.0002123858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.591269,"threshold_uncertainty_score":0.9999539,"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."}}