{"id":"W2171380912","doi":"10.1002/sim.969","title":"A model for foetal growth and diagnosis of intrauterine growth restriction","year":2001,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Birth, Development, and Health","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gestational age; Intrauterine growth restriction; Fetal growth; Residual; Pregnancy; Fetus; Growth model; Birth weight; Covariance; Obstetrics; Growth curve (statistics); Medicine; Statistics; Mathematics; Biology; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006380804,0.001761132,0.001996251,0.00235446,0.0008408253,0.002665802,0.004001448,0.003666214,0.01025881],"category_scores_gemma":[0.01801213,0.001073399,0.00180012,0.002325,0.00168003,0.002011054,0.001754818,0.003557688,0.003644698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002728067,"about_ca_system_score_gemma":0.003135952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02573174,"about_ca_topic_score_gemma":0.01274402,"domain_scores_codex":[0.9965106,0.001595028,0.0001350433,0.0009031986,0.0004023044,0.0004537825],"domain_scores_gemma":[0.9882957,0.008845361,0.001240743,0.0004860228,0.0007951844,0.0003371967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007235452,0.0002638016,0.03111374,0.0002324447,0.0006104517,0.001002278,0.0005552716,0.7179924,0.001517492,0.1899969,0.01052584,0.04546587],"study_design_scores_gemma":[0.0002655346,0.0002221623,0.006173837,0.00007245329,0.000154659,0.0004685368,0.00008352471,0.9215696,0.0002437545,0.06388149,0.006770568,0.00009374748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07739981,0.001331683,0.8965586,0.005985755,0.0003418146,0.000442667,0.0092729,0.001208688,0.007458172],"genre_scores_gemma":[0.761033,0.002602376,0.1640058,0.0007918226,0.0004978518,0.003011688,0.01155758,0.0003326674,0.05616718],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02573174,"threshold_uncertainty_score":0.05116391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04616301159606384,"score_gpt":0.3457173785637733,"score_spread":0.2995543669677094,"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."}}