{"id":"W3019427358","doi":"10.1590/0001-3765202020180697","title":"Genetic parameters for performance and carcass traits in a paternal 1 lineage of broiler","year":2020,"lang":"pt","type":"article","venue":"Anais da Academia Brasileira de Ciências","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidade Estadual Paulista; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Empresa Brasileira de Pesquisa Agropecuária; Fundação de Amparo à Pesquisa do Estado de São Paulo; University of Guelph","keywords":"Heritability; Biology; Genetic correlation; Restricted maximum likelihood; Selection (genetic algorithm); Broiler; Genetic gain; Weight gain; Animal science; Feed conversion ratio; Genetic variation; Statistics; Body weight; Genetics; Maximum likelihood; Mathematics; Gene; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005087538,0.0003951129,0.0001507438,0.0005790725,0.0001524375,0.0002502724,0.0001601491,0.0001990791,0.0005933984],"category_scores_gemma":[0.00101315,0.0001878006,0.0002337348,0.0002552845,0.0001459289,0.0001009088,0.0001432811,0.0002718608,0.000150993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001558858,"about_ca_system_score_gemma":0.0001522034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002601688,"about_ca_topic_score_gemma":0.004437895,"domain_scores_codex":[0.9996811,0.0001106922,0.00001793687,0.0001097049,0.00006038546,0.00002003869],"domain_scores_gemma":[0.9993771,0.0002504395,0.0001988067,0.00006076581,0.00006620058,0.0000466507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007211562,0.0001166793,0.7237093,0.00005727577,0.0003457858,0.0005196399,0.0005150643,0.00356199,0.2471522,0.0003622836,0.00007066168,0.02286798],"study_design_scores_gemma":[0.000008081304,0.0001344538,0.9920351,0.000007250158,0.00006491793,0.0003902246,0.00005618007,0.004056518,0.002977787,0.00006331741,0.0001963952,0.000009754014],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979531,0.00004182738,0.001825468,0.000004521361,9.193799e-7,0.000002263352,0.00008504091,0.00000617201,0.00008064076],"genre_scores_gemma":[0.9962624,0.00003512243,0.002948751,0.000005372578,0.00000181105,0.000005638909,0.0003817674,0.00001467073,0.0003445774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002601688,"threshold_uncertainty_score":0.005173087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06348801168031078,"score_gpt":0.2692252050519064,"score_spread":0.2057371933715956,"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."}}