{"id":"W4402405672","doi":"10.23889/ijpds.v9i5.2758","title":"Data Quality Implications in Research when Transitioning to a New Electronic Medical Record","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Alberta Health","funders":"","keywords":"Quality (philosophy); Electronic medical record; Data quality; Computer science; Data science; Business; Internet privacy; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06448714,0.00009622802,0.0001580399,0.001697912,0.0004480219,0.003472881,0.01395098,0.00004952095,0.0006111655],"category_scores_gemma":[0.02743388,0.00008042308,0.00004078944,0.002156704,0.0001496161,0.007474051,0.002569062,0.0004963501,0.000185414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004396839,"about_ca_system_score_gemma":0.001796553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002169358,"about_ca_topic_score_gemma":0.01213964,"domain_scores_codex":[0.9910117,0.0003422914,0.001246243,0.0011813,0.005722623,0.0004958822],"domain_scores_gemma":[0.9945937,0.001962543,0.0001576728,0.002007676,0.0008642442,0.000414114],"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":[0.00005465957,0.00005570337,0.00155892,0.000003961621,0.00001776996,0.000007878547,0.0004007451,0.0001395601,0.0001415858,0.2913127,0.1531366,0.5531699],"study_design_scores_gemma":[0.0002137588,0.00003498851,0.01956708,0.0001008562,0.000004121701,0.00003869272,0.0003039589,0.03159301,0.000004994936,0.3163813,0.6316465,0.0001108149],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01756782,0.0001081076,0.8088138,0.1669619,0.003054628,0.00046998,0.002317967,0.00004445776,0.0006613642],"genre_scores_gemma":[0.943832,0.0001914468,0.04540999,0.00250774,0.001790895,0.00003350116,0.003505229,0.00002234078,0.002706873],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9262642,"threshold_uncertainty_score":0.9975616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7950921562511286,"score_gpt":0.6891429991574641,"score_spread":0.1059491570936645,"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."}}