{"id":"W4413684012","doi":"10.2196/70066","title":"Integration of Data and Information Systems Into the Health Data Strategy","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Czech; Computer science; Data science; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.004519491,0.00007991883,0.0002073924,0.0001689987,0.000173337,0.0003078131,0.004234876,0.0001262132,0.00001561071],"category_scores_gemma":[0.002416897,0.0000417462,0.00001058164,0.0008694121,0.0003166831,0.003498927,0.002602425,0.0002612235,0.00003040006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001760934,"about_ca_system_score_gemma":0.0003890432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002017949,"about_ca_topic_score_gemma":0.0001179065,"domain_scores_codex":[0.9971936,0.00005614715,0.001421072,0.0001196825,0.001081959,0.0001275051],"domain_scores_gemma":[0.9956959,0.000629988,0.0005390335,0.002898161,0.0001643048,0.00007254723],"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":[0.000002792466,0.00001160923,0.00003976969,0.00005225995,0.00000642736,2.450048e-8,0.0009829474,0.000002847478,8.210528e-7,0.08390244,0.1221016,0.7928964],"study_design_scores_gemma":[0.0001511487,0.00003166755,0.0005509912,0.00009262055,0.000004689763,0.000003157542,0.03218131,0.381504,0.000004265774,0.003890864,0.5815386,0.00004668764],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03337098,0.001303937,0.8948914,0.0546278,0.0005239894,0.002137417,0.002128614,0.0002139361,0.01080188],"genre_scores_gemma":[0.983977,0.001464187,0.008455643,0.003091347,0.00004117326,0.0000616746,0.002810851,0.000003371691,0.00009478893],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.950606,"threshold_uncertainty_score":0.7869523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2641624079056417,"score_gpt":0.4708056528706074,"score_spread":0.2066432449649657,"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."}}