{"id":"W2120027488","doi":"10.1111/j.1541-0420.2011.01648.x","title":"Constructing Normalcy and Discrepancy Indexes for Birth Weight and Gestational Age Using a Threshold Regression Mixture Model","year":2011,"lang":"en","type":"article","venue":"Biometrics","topic":"Birth, Development, and Health","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Ottawa Hospital","funders":"National Institute for Occupational Safety and Health; National Institutes of Health; World Health Organization","keywords":"Birth weight; Gestational age; Medicine; Regression analysis; Statistics; Population; Gestation; Obstetrics; Pregnancy; Demography; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002283138,0.0001311046,0.0002203544,0.0008074864,0.0001777986,0.00002111856,0.00003513218,0.0001350136,0.000008632026],"category_scores_gemma":[0.0001211149,0.00009828898,0.00002663587,0.0007709372,0.0001017056,0.0001144339,0.00004728229,0.0001182797,3.376261e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005127007,"about_ca_system_score_gemma":0.0001731265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002644161,"about_ca_topic_score_gemma":0.00001095635,"domain_scores_codex":[0.9990943,0.000008597155,0.0002310835,0.0002416604,0.0001926019,0.0002317315],"domain_scores_gemma":[0.9994357,0.00006009731,0.0001290461,0.00009871966,0.0001012976,0.0001751126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002928693,0.0001301632,0.8554773,0.001204808,0.00006701106,0.00003551566,0.002920104,4.720378e-7,0.002231341,0.10554,0.0002927574,0.03180758],"study_design_scores_gemma":[0.01453568,0.001084274,0.7398078,0.001734432,0.0004601244,0.001082414,0.002368147,0.1040956,0.00778468,0.1237712,0.001746652,0.001528965],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819481,0.001733078,0.0144762,0.0001365149,0.0001265578,0.0003649957,0.0000671166,0.0000353605,0.001112026],"genre_scores_gemma":[0.7669402,0.004933083,0.2277313,0.0001975576,0.00007777114,0.000007248107,0.00003702507,0.00001850646,0.00005722553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2150079,"threshold_uncertainty_score":0.4008108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09953518730539902,"score_gpt":0.3264595443720438,"score_spread":0.2269243570666448,"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."}}