{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2435332,0.0009828302,0.003169829,0.01368934,0.001928782,0.005525567,0.005034554,0.002177479,0.002505798],"category_scores_gemma":[0.4437844,0.002037283,0.002528855,0.02155222,0.00163098,0.007334611,0.009192199,0.002689305,0.0007985883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003904895,"about_ca_system_score_gemma":0.01713237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04982506,"about_ca_topic_score_gemma":0.03522984,"domain_scores_codex":[0.6865711,0.2202026,0.04519195,0.01345004,0.02890927,0.005674979],"domain_scores_gemma":[0.4487057,0.250392,0.0899002,0.1227739,0.08512339,0.003104779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005045542,0.0003184426,0.875287,0.001329927,0.001553968,0.0001119887,0.003945116,0.003357441,0.001454516,0.004318346,0.006614514,0.1012043],"study_design_scores_gemma":[0.0003140107,0.0004763803,0.9491102,0.001362219,0.001836715,0.0003909742,0.001937942,0.01543617,0.003485556,0.005606434,0.01983293,0.0002104984],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5467981,0.0107661,0.3654,0.01293458,0.0006297734,0.00666366,0.03698121,0.001436288,0.01839032],"genre_scores_gemma":[0.7956905,0.00266326,0.1705206,0.001638441,0.0004447887,0.002092604,0.02530103,0.0002785856,0.001370228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2435332,"threshold_uncertainty_score":0.9328583,"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."}}