{"id":"W4416786188","doi":"10.1111/jan.70405","title":"Understanding Digital Health Equity: A Conceptual Analysis","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Nursing","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Digital health; Public health; Formal concept analysis; MEDLINE; Conceptual framework; mHealth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001132134,0.0001478432,0.0006841702,0.0007904458,0.001137653,0.00002320347,0.0002264944,0.0001178606,0.00006824828],"category_scores_gemma":[0.0003460187,0.0001346837,0.0002110988,0.001740555,0.0001488954,0.0003701856,0.00004678917,0.0008799944,0.00001086518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003065109,"about_ca_system_score_gemma":0.00268415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009067015,"about_ca_topic_score_gemma":0.00003179004,"domain_scores_codex":[0.9969146,0.0002157847,0.001570408,0.0002054479,0.0003514303,0.0007423664],"domain_scores_gemma":[0.9968316,0.0007256526,0.001388468,0.0002580388,0.0003056878,0.0004905641],"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":[0.000877167,0.0004480659,0.01637946,0.0006515759,0.0005539736,0.000009148242,0.007023506,0.002912754,0.0001583632,0.3115898,0.05308487,0.6063113],"study_design_scores_gemma":[0.01026853,0.00125641,0.0255596,0.008882661,0.001101502,0.00003105452,0.2171421,0.001168179,0.00003302767,0.1737404,0.5601837,0.0006328275],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02220765,0.005751295,0.8531134,0.04239002,0.003620456,0.002271384,0.00005948048,0.0001186869,0.07046761],"genre_scores_gemma":[0.9906384,0.0005710488,0.00382923,0.003904729,0.0003077072,0.00007027401,0.00001334664,0.00001578482,0.0006495093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9684307,"threshold_uncertainty_score":0.8750022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1714223596394754,"score_gpt":0.5235959326452995,"score_spread":0.3521735730058241,"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."}}