{"id":"W2107724629","doi":"10.1002/sim.1095","title":"Detecting and eliminating erroneous gestational ages: a normal mixture model","year":2001,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Birth, Development, and Health","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; Dalhousie University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Gestational age; Birth weight; Medicine; Obstetrics; Population; Small for gestational age; Gestation; Pregnancy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005865045,0.000159152,0.0003301369,0.0002006779,0.0001302931,0.000006910593,0.00004784826,0.00009307286,0.0001120019],"category_scores_gemma":[0.001012875,0.0001364688,0.000009897368,0.0001931372,0.0001503845,0.00004012783,0.00002762573,0.0004607005,0.000004543657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001070685,"about_ca_system_score_gemma":0.0001913731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001523557,"about_ca_topic_score_gemma":0.00045131,"domain_scores_codex":[0.9985098,0.00003351017,0.0004518029,0.0002572919,0.0003962104,0.0003513792],"domain_scores_gemma":[0.9991211,0.0003098229,0.0001168436,0.0001191056,0.0001379853,0.0001950841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001283577,0.0004925106,0.2233402,0.003720703,0.0001731609,0.005755759,0.05843152,0.001203145,0.005218579,0.28333,0.02015166,0.3968992],"study_design_scores_gemma":[0.01081141,0.001475058,0.3259441,0.002078634,0.0002114283,0.002465842,0.005821019,0.4919055,0.0000833613,0.1576881,0.0008560518,0.0006596049],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5692176,0.00133669,0.4006015,0.007202766,0.0004004943,0.0008001202,0.00008233287,0.0001172078,0.02024131],"genre_scores_gemma":[0.8074844,0.009424203,0.1803167,0.002146811,0.0002420812,0.00001513962,0.0001133232,0.00002642546,0.0002309004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4907023,"threshold_uncertainty_score":0.5565037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03034987883830143,"score_gpt":0.3359374601667724,"score_spread":0.305587581328471,"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."}}