{"id":"W4407912048","doi":"10.2196/70149","title":"Digital Health Platform for Maternal Health: Design, Recruitment Strategies, and Lessons Learned From the PowerMom Observational Cohort Study","year":2025,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Observational study; Digital health; Psychology; Computer science; Medicine; Health care; World Wide Web; Political science","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":[0.1058469,0.0007172187,0.0007064696,0.001860811,0.003290073,0.002783691,0.002385418,0.001412992,0.007253508],"category_scores_gemma":[0.117856,0.0009561841,0.00124368,0.002247923,0.001545362,0.003721746,0.005421734,0.002351846,0.002172547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002507806,"about_ca_system_score_gemma":0.01675039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01007115,"about_ca_topic_score_gemma":0.02404927,"domain_scores_codex":[0.9422736,0.04704694,0.003154686,0.001543976,0.004249971,0.001730885],"domain_scores_gemma":[0.9509759,0.02655645,0.00259112,0.00766352,0.009364135,0.002848882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00494945,0.008793258,0.37154,0.004941895,0.0005901689,0.003047681,0.08114227,0.00158127,0.002238921,0.01761347,0.09481125,0.4087503],"study_design_scores_gemma":[0.01045752,0.02670955,0.3859854,0.01740496,0.001648165,0.003041551,0.1088893,0.01173307,0.005123269,0.0323774,0.3958409,0.0007889543],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5786163,0.003330278,0.1357821,0.02941555,0.001662505,0.2119749,0.0140736,0.0006563618,0.02448845],"genre_scores_gemma":[0.3893411,0.00301187,0.2047177,0.01026283,0.0007481289,0.3833996,0.003517425,0.0003749685,0.004626292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1058469,"threshold_uncertainty_score":0.5597787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5515509876217828,"score_gpt":0.599297288029145,"score_spread":0.04774630040736216,"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."}}