{"id":"W4296025051","doi":"10.12688/gatesopenres.13131.2","title":"External validation of machine learning models including newborn metabolomic markers for postnatal gestational age estimation in East and South-East Asian infants","year":2021,"lang":"en","type":"preprint","venue":"Gates Open Research","topic":"Birth, Development, and Health","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bruyère; Newborn Screening Ontario; Children's Hospital of Eastern Ontario; Ontario Stroke Network; Ottawa Hospital; University of Ottawa","funders":"Bill and Melinda Gates Foundation","keywords":"Gestational age; Birth weight; Medicine; Population; Cohort; Low birth weight; Obstetrics; Demography; Pregnancy; Biology; Internal medicine; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004412063,0.0002156572,0.0006009056,0.0006626556,0.0002340582,0.0002790842,0.0003088629,0.000234405,0.00008377658],"category_scores_gemma":[0.0007720601,0.0002184738,0.00005918927,0.0002807728,0.0001159249,0.0003392244,0.001312195,0.001277554,0.000003122863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002395659,"about_ca_system_score_gemma":0.001516317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001594712,"about_ca_topic_score_gemma":0.0002906551,"domain_scores_codex":[0.9970448,0.0004420192,0.0006624486,0.0006166427,0.0007764059,0.0004576822],"domain_scores_gemma":[0.998553,0.0001740225,0.0002725257,0.0002467233,0.0005562443,0.0001974431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01900203,0.001196943,0.5192832,0.0206127,0.001357221,0.0006679828,0.1322313,0.07086096,0.0210553,0.02565803,0.0002912289,0.1877831],"study_design_scores_gemma":[0.005681899,0.0002886101,0.4673696,0.004301399,0.00007618709,0.00008039083,0.007441524,0.4854848,0.001228064,0.0275936,0.00002346704,0.0004303604],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840157,0.0006512988,0.008578208,0.00127057,0.00008524285,0.003015453,0.0001796206,0.00001626473,0.002187649],"genre_scores_gemma":[0.9209359,0.001776101,0.07441794,0.00002835659,0.00004367888,0.0002421029,0.002419059,0.00004167809,0.00009517064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4146239,"threshold_uncertainty_score":0.8909104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2031240169796311,"score_gpt":0.427449674996679,"score_spread":0.224325658017048,"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."}}