{"id":"W3176482524","doi":"10.1096/fasebj.2019.33.1_supplement.330.2","title":"Integration and the genetics of variation in facial shape","year":2019,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Morphological variations and asymmetry","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Variation (astronomy); Biology; Heritability; Evolutionary biology; Genetic variation; Genetics; Genetic architecture; Craniofacial; Quantitative genetics; Population; Quantitative trait locus; Gene; Demography","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":[0.0006950764,0.0003048262,0.0003345177,0.0009037111,0.0002930542,0.0007910667,0.0003480779,0.0005506832,0.001695397],"category_scores_gemma":[0.001536708,0.0003120298,0.0002627912,0.0005952343,0.001287012,0.0003694982,0.0008614295,0.0004798387,0.0001701658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004435291,"about_ca_system_score_gemma":0.0003165645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003010484,"about_ca_topic_score_gemma":0.002983779,"domain_scores_codex":[0.9991133,0.0002937845,0.000032989,0.0002284647,0.0002625267,0.00006896053],"domain_scores_gemma":[0.9993482,0.0002960058,0.000175754,0.00006554322,0.00005300264,0.00006143197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001187661,0.000400046,0.295251,0.0002354608,0.0007190466,0.002743788,0.002173327,0.008357402,0.4252067,0.04333226,0.001735007,0.2186582],"study_design_scores_gemma":[0.00005435367,0.0001584686,0.9602613,0.00004170959,0.000162419,0.001276297,0.0004320022,0.005303147,0.005450301,0.02504799,0.001751134,0.00006086144],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861829,0.00146949,0.006426805,0.0007129455,0.00002952299,0.00001521846,0.0001467534,0.00006231882,0.004953998],"genre_scores_gemma":[0.995389,0.0006201068,0.002221476,0.0001167615,0.00002546809,0.00001876646,0.0000881895,0.00002904561,0.001491041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003010484,"threshold_uncertainty_score":0.005985916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03219707940603546,"score_gpt":0.2723857858287666,"score_spread":0.2401887064227312,"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."}}