{"id":"W3130084604","doi":"10.1016/j.psj.2021.101062","title":"Modeling genetic components of hatch of fertile in broiler breeders","year":2021,"lang":"en","type":"article","venue":"Poultry Science","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Repeatability; Heritability; Statistics; Selection (genetic algorithm); Trait; Regression analysis; Regression; Biology; Random effects model; Linear regression; Genetic correlation; Animal model; Animal science; Broiler; Mathematics; Genetic variation; Medicine; Computer science; Genetics","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":[0.0001022776,0.00004590118,0.0001141629,0.00001302051,0.00004364493,0.000007302073,0.0002059984,0.00002927241,0.0001381958],"category_scores_gemma":[0.00003947315,0.00002068722,0.0000334866,0.000559488,0.0001689333,0.00007185121,0.00006001114,0.00004533693,0.000005952176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007716341,"about_ca_system_score_gemma":0.000016318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000527049,"about_ca_topic_score_gemma":0.0001036646,"domain_scores_codex":[0.9993039,0.00002885841,0.0001718124,0.0001801809,0.0001652612,0.0001500237],"domain_scores_gemma":[0.99973,0.0000393072,0.00003658172,0.00003811618,0.0001127767,0.00004320233],"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":[0.00001078393,0.00007254325,0.04882553,0.000005048325,5.852852e-7,9.290895e-7,0.00003759073,0.0004819036,0.9490312,0.00009104473,0.000007561344,0.001435232],"study_design_scores_gemma":[0.0001028898,0.00006245384,0.9713924,0.00003059747,0.000001222455,0.000003454433,0.0006855312,0.01137516,0.0154489,0.0007844802,0.00004813537,0.0000647698],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989502,0.000103531,0.0000113626,0.0002470315,0.00004142615,0.00003360987,0.000007698581,0.000004753193,0.0006003188],"genre_scores_gemma":[0.9995013,0.0000290707,0.0003124237,0.0001124695,0.00001333544,9.046788e-7,0.000006025218,2.145874e-7,0.00002426192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9335824,"threshold_uncertainty_score":0.1513148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04046358083939949,"score_gpt":0.2380393601579455,"score_spread":0.197575779318546,"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."}}