{"id":"W2762327806","doi":"10.1093/pch/9.suppl_a.39aa","title":"67 A Population-Based Delivery-Based Longitudinal Maternal-Child Health Database","year":2004,"lang":"en","type":"article","venue":"Paediatrics & Child Health","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Database; Identifier; Confidentiality; Population; Unique identifier; Computer science; Medicine; Environmental health; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004000124,0.0002563034,0.000598648,0.005995636,0.001035129,0.001534059,0.001441516,0.0005063137,0.01651163],"category_scores_gemma":[0.01174099,0.0006260367,0.000376035,0.00809458,0.0001790367,0.0006768184,0.00163603,0.0007822053,0.01024243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00356853,"about_ca_system_score_gemma":0.01646928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09617724,"about_ca_topic_score_gemma":0.09326162,"domain_scores_codex":[0.9964593,0.0007702959,0.001084858,0.0005176491,0.0009231464,0.0002447805],"domain_scores_gemma":[0.9906336,0.001489777,0.001581969,0.001627792,0.003638669,0.001028137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001030379,0.0005530305,0.3467143,0.001644853,0.0002197415,0.0009769213,0.001637058,0.001299054,0.002614835,0.01261258,0.4857907,0.1449065],"study_design_scores_gemma":[0.0004730875,0.0003150988,0.5798671,0.0008088651,0.0001769557,0.0007043649,0.0007872962,0.002491919,0.00141462,0.0009963543,0.4118784,0.00008605044],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.03850282,0.0005129855,0.009829499,0.0009122187,0.0001358597,0.004541722,0.9202906,0.0007140604,0.02456019],"genre_scores_gemma":[0.08897796,0.001160739,0.02660463,0.0007032526,0.0001419472,0.009951359,0.8602782,0.0001475382,0.01203433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09617724,"threshold_uncertainty_score":0.1912348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0343426391036754,"score_gpt":0.3733060041281822,"score_spread":0.3389633650245067,"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."}}