{"id":"W4414875195","doi":"10.2196/75275","title":"Assessing Data Quality in Heterogeneous Health Care Integration: Simulation Study of the AIDAVA Framework","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Software deployment; Health care; Data quality; Health data; Quality (philosophy); Work (physics); Data collection; Data validation","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":[0.01515944,0.000931565,0.0008087075,0.001755849,0.001021738,0.001980476,0.002470599,0.001976131,0.002023329],"category_scores_gemma":[0.04227321,0.0006636237,0.001592435,0.002047197,0.001761211,0.00187058,0.002508957,0.002069782,0.0001464164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006535091,"about_ca_system_score_gemma":0.004496986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1078672,"about_ca_topic_score_gemma":0.06744565,"domain_scores_codex":[0.994525,0.003611224,0.0002129666,0.0006080295,0.0005894665,0.0004534019],"domain_scores_gemma":[0.9364266,0.0536994,0.002349999,0.002676541,0.003634185,0.001213201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001989359,0.0002743046,0.01613344,0.00007994794,0.00009763288,0.0001499388,0.0002545372,0.9708574,0.0002183958,0.006455559,0.0008002769,0.004479632],"study_design_scores_gemma":[0.0000975006,0.000157603,0.002274763,0.00002575553,0.00003767528,0.00003329836,0.0002372157,0.9931751,0.0002591154,0.003024779,0.0006590948,0.00001817022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9565584,0.0003421955,0.03284387,0.001193712,0.0000499076,0.0005209479,0.001906163,0.0003145828,0.006270215],"genre_scores_gemma":[0.9580747,0.000117527,0.0394511,0.000157978,0.000007590881,0.0002771937,0.001268811,0.0000368433,0.0006082633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1078672,"threshold_uncertainty_score":0.2144786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1719436036649179,"score_gpt":0.5923950400856313,"score_spread":0.4204514364207134,"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."}}