{"id":"W2162429877","doi":"10.1111/j.1471-0528.2008.01870.x","title":"Customised birthweight percentiles: does adjusting for maternal characteristics matter?","year":2008,"lang":"en","type":"article","venue":"BJOG An International Journal of Obstetrics & Gynaecology","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Obstetrics; Percentile; Gestational age; Small for gestational age; Population; Birth weight; Body mass index; Parity (physics); Pregnancy; Cohort; Pediatrics; Demography; Statistics; Environmental health; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.01487928,0.000792171,0.001187298,0.001112582,0.0003513003,0.001321322,0.001503181,0.001156557,0.001950087],"category_scores_gemma":[0.06804949,0.0004416167,0.001883265,0.003600293,0.000714226,0.001820124,0.0007800828,0.001232343,0.0003891126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003513565,"about_ca_system_score_gemma":0.0007205774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004748971,"about_ca_topic_score_gemma":0.004600503,"domain_scores_codex":[0.9913098,0.004731295,0.0008249431,0.001690914,0.00105045,0.0003926702],"domain_scores_gemma":[0.9598405,0.02148159,0.01026724,0.006385189,0.001110603,0.0009148538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003957506,0.000021345,0.9809211,0.00007165082,0.001174381,0.00008133781,0.0001249585,0.0004935121,0.00009415888,0.000178315,0.0004618197,0.01598158],"study_design_scores_gemma":[0.00002891333,0.0003054528,0.9939402,0.0001195085,0.0008605604,0.0002578775,0.0001198136,0.002432127,0.000170534,0.000726763,0.001016421,0.00002185726],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9709151,0.0116544,0.009019963,0.002741217,0.0004396061,0.00008261009,0.00186979,0.0001739351,0.003103541],"genre_scores_gemma":[0.996241,0.0008221468,0.001749859,0.0002038959,0.0001110005,0.00002314941,0.0005737094,0.00004763615,0.0002275304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01487928,"threshold_uncertainty_score":0.07869011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02557605528798378,"score_gpt":0.3086320690701158,"score_spread":0.283056013782132,"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."}}