{"id":"W2091934576","doi":"10.1016/j.annepidem.2013.05.002","title":"Improving completeness of ascertainment and quality of information for pregnancies through linkage of administrative and clinical data records","year":2013,"lang":"en","type":"article","venue":"Annals of Epidemiology","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba; Saskatchewan Health Authority; University of Calgary; University of Saskatchewan; University of British Columbia","funders":"Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; Government of Alberta; Calgary Laboratory Services","keywords":"Medicine; Record linkage; Pregnancy; Cohort; Medical record; Data quality; Linkage (software); Epidemiology; Obstetrics; Cohort study; Live birth; Retrospective cohort study; Medical emergency; Population; Environmental health; Surgery; Operations management; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002778575,0.00007016173,0.0008532595,0.00002089536,0.0000140475,6.592979e-7,0.00008636798,0.00009851233,0.000008011103],"category_scores_gemma":[0.005148133,0.00004994278,0.00005128413,0.00002643091,0.0003281216,0.0001541121,0.0001050975,0.00006537663,1.919334e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000240996,"about_ca_system_score_gemma":0.00006359732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004067637,"about_ca_topic_score_gemma":0.0000418315,"domain_scores_codex":[0.997921,0.0002612278,0.001492342,0.0001263398,0.0000588754,0.000140237],"domain_scores_gemma":[0.9961212,0.002074041,0.00116018,0.0002656584,0.0003177962,0.00006116641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007223943,0.0001850172,0.9523916,0.005279216,0.0001611234,8.929045e-8,0.0003532766,0.000001052311,0.0005039187,0.01469125,0.001167451,0.02454362],"study_design_scores_gemma":[0.0007712577,0.002184159,0.9880939,0.0003253615,0.00003643343,0.000002478899,0.0003917913,0.0004004134,0.0008606833,0.00622309,0.0006677562,0.00004274113],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928935,0.0009280097,0.002000125,0.003139766,0.00004519526,0.0004749897,0.0003438812,0.000002553058,0.000172041],"genre_scores_gemma":[0.9880345,0.001833843,0.008661957,0.001335882,0.00002371719,0.000005915054,0.00009596925,0.000002098921,0.00000608236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03570223,"threshold_uncertainty_score":0.6163167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5549626448715332,"score_gpt":0.5430792584697952,"score_spread":0.01188338640173803,"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."}}