{"id":"W4414571598","doi":"10.1016/j.bglo.2025.100031","title":"Development of disease-specific growth curves from Kenyan children with sickle cell anemia","year":2025,"lang":"en","type":"article","venue":"Blood Global Hematology","topic":"Hemoglobinopathies and Related Disorders","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University of Toronto","funders":"National Heart, Lung, and Blood Institute; Cincinnati Children’s Research Foundation; Wellcome Trust","keywords":"Percentile; Sickle cell anemia; Cohort; Body mass index; Anemia; Growth curve (statistics); Hemoglobinopathy; Kenya; Anthropometry","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":[0.002230168,0.0006604758,0.0003343631,0.003478931,0.0006007344,0.0007379952,0.0005034382,0.0003174561,0.00191473],"category_scores_gemma":[0.005796841,0.0002318128,0.0006099008,0.003286972,0.0002165127,0.0006381682,0.0008152821,0.0004698891,0.0006747208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115835,"about_ca_system_score_gemma":0.0009191796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05403874,"about_ca_topic_score_gemma":0.05746241,"domain_scores_codex":[0.9992907,0.0001996568,0.0001012637,0.0001147777,0.0001874002,0.0001062482],"domain_scores_gemma":[0.9976709,0.0003594015,0.00060518,0.0002392181,0.0009909718,0.000134358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003231929,0.00005517286,0.951772,0.0001270841,0.00008246378,0.0001908592,0.001038498,0.002487311,0.001769395,0.0004348479,0.002867947,0.03885134],"study_design_scores_gemma":[0.000009217491,0.0001386845,0.9922563,0.0000551702,0.00001902659,0.0003408988,0.0006449205,0.001837255,0.0006601679,0.000092915,0.003926034,0.00001944963],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9694856,0.0004464224,0.005546275,0.0001225502,0.00002488752,0.0002598558,0.018818,0.0001804511,0.005115962],"genre_scores_gemma":[0.9628966,0.000558957,0.01356558,0.00004371873,0.000009977779,0.0005202309,0.02135235,0.00008514826,0.0009674578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05403874,"threshold_uncertainty_score":0.1074484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005731217249240616,"score_gpt":0.2187145543802602,"score_spread":0.2129833371310196,"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."}}