{"id":"W2793020645","doi":"10.1017/s175173111800023x","title":"Pedigree analysis and inbreeding effects over morphological traits in Campolina horse population","year":2018,"lang":"en","type":"article","venue":"animal","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; BIO (Canada)","funders":"","keywords":"Inbreeding; Inbreeding depression; Biology; Population; Effective population size; Statistics; Genetic variation; Genetics; 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":[0.00008635985,0.0001037566,0.0001311261,0.00007065892,0.00004627667,0.00001256736,0.00007226559,0.0001379925,0.00002665129],"category_scores_gemma":[0.00004912685,0.00009397537,0.00004616639,0.0001689279,0.00008374327,0.000003175756,0.00006202938,0.00006110314,0.000003080568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005660007,"about_ca_system_score_gemma":0.000008684692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001657762,"about_ca_topic_score_gemma":0.0003675427,"domain_scores_codex":[0.9993102,0.00003730907,0.0001251119,0.0002784845,0.00007209004,0.0001768262],"domain_scores_gemma":[0.999778,0.00001350276,0.00003543069,0.00009585365,0.00002005045,0.0000571272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001721822,0.0000613081,0.8282805,0.00001116973,0.00008800683,0.000003997006,0.0001759235,0.00002142248,0.1663208,0.0009827119,0.0003071242,0.003574865],"study_design_scores_gemma":[0.0003301545,0.0007558675,0.9947805,0.000003882131,0.00006808433,0.000007599994,0.00001385939,0.00006221313,0.003375971,0.0003801062,0.0001040637,0.0001177359],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982112,0.000154887,0.001060702,0.00002337872,0.00004670494,0.00009033883,0.000005784976,0.000007240033,0.0003997728],"genre_scores_gemma":[0.9954616,0.000008018285,0.003950185,0.0001149602,0.0003566227,0.000005565124,0.00003331458,0.000007529703,0.00006218721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1665,"threshold_uncertainty_score":0.3832205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009239819071339875,"score_gpt":0.2571970112965521,"score_spread":0.2479571922252123,"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."}}