{"id":"W4417230801","doi":"10.1111/birt.70037","title":"Next‐Gen Midwifery Support: Designing an Artificial Intelligence ( <scp>AI</scp> ) Enhanced Mobile App for Pregnancy Risk Categorization and Clinical Decision Support on Maternal and Neonatal Outcomes","year":2025,"lang":"en","type":"article","venue":"Birth","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Categorization; Decision support system; Psychological intervention; Mobile apps; Pregnancy; mHealth; Risk assessment","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007195306,0.0002288071,0.0004042811,0.0002237236,0.0002850926,0.0001194758,0.0001105895,0.0002496792,0.00003781631],"category_scores_gemma":[0.001331107,0.0001998166,0.00008883895,0.0002033885,0.0001346655,0.0002919402,0.00004692259,0.0002836401,0.00002972697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005921229,"about_ca_system_score_gemma":0.0003490039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000145786,"about_ca_topic_score_gemma":0.0001478104,"domain_scores_codex":[0.9977186,0.00009981367,0.0009696831,0.0006090236,0.0002298587,0.0003730008],"domain_scores_gemma":[0.997676,0.001278292,0.0002281814,0.0003149497,0.0002470661,0.0002555585],"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":[0.0002779333,0.0001684547,0.1365027,0.0001295929,0.00003430384,0.000006725623,0.00137396,0.00003741397,0.000330482,0.0009979184,0.0001360771,0.8600044],"study_design_scores_gemma":[0.0008562863,0.01291477,0.2558603,0.001753904,0.0006602523,0.00006587977,0.01554585,0.02208995,0.5988138,0.0856358,0.005146908,0.0006563627],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7805648,0.0002255696,0.2168394,0.000153395,0.0009246967,0.001130432,0.00002381444,0.00007374887,0.00006402693],"genre_scores_gemma":[0.9927102,0.001152912,0.004495261,0.0005364633,0.0002836125,0.0001867622,0.00009253376,0.0000290725,0.0005131287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8593481,"threshold_uncertainty_score":0.8148285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09726595510743101,"score_gpt":0.4366934826585346,"score_spread":0.3394275275511036,"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."}}