{"id":"W2029254935","doi":"10.2527/jas.2007-0234","title":"Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle1","year":2007,"lang":"en","type":"article","venue":"Journal of Animal Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture Food and Rural Development; Agriculture and Agri-Food Canada; University of Alberta","funders":"","keywords":"Quantitative trait locus; Residual feed intake; Biology; Sire; Feedlot; Animal science; Microsatellite; Autosome; Beef cattle; Chromosome; Feed conversion ratio; Genetics; Allele; Gene; Body weight","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007945169,0.0004906216,0.0008525281,0.00135629,0.0005538595,0.0005345086,0.0006698332,0.0003961169,0.005627834],"category_scores_gemma":[0.0009066435,0.0003238737,0.0008658139,0.002006649,0.0002011595,0.0001100421,0.000414203,0.0005701407,0.0005958371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008722188,"about_ca_system_score_gemma":0.001334665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05827106,"about_ca_topic_score_gemma":0.1178043,"domain_scores_codex":[0.9994335,0.00007674783,0.0000156497,0.0002569315,0.0001372029,0.00007993156],"domain_scores_gemma":[0.9993094,0.0001868117,0.0001157999,0.00005804024,0.000170115,0.0001598234],"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":[0.004113885,0.0007650562,0.376637,0.0009453141,0.003085503,0.002620441,0.0009827788,0.001732449,0.5347016,0.0008912568,0.007048892,0.06647577],"study_design_scores_gemma":[0.00009731309,0.000339188,0.9903032,0.00001944796,0.0003823043,0.0005567271,0.00006545927,0.0009891868,0.003146905,0.00007656147,0.004014506,0.000009294837],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9494318,0.003411822,0.01620349,0.000326546,0.0000526594,0.0003028666,0.0248581,0.0009168045,0.004495936],"genre_scores_gemma":[0.9475208,0.0006058562,0.02190482,0.0004597964,0.00002784911,0.0002022743,0.02295238,0.0001210089,0.006205186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05827106,"threshold_uncertainty_score":0.1158637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964173102011938,"score_gpt":0.3065009007796511,"score_spread":0.2868591697595317,"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."}}