{"id":"W2019862819","doi":"10.1111/j.1365-2052.2006.01512.x","title":"Marker‐assisted selection based on a multi‐trait economic index in chicken: experimental results and simulation","year":2006,"lang":"en","type":"article","venue":"Animal Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"","keywords":"Sire; Biology; Trait; Selection (genetic algorithm); Heritability; Quantitative trait locus; Marker-assisted selection; Statistics; Value (mathematics); Genetics; Index selection; Index (typography); Evolutionary biology; Gene; Mathematics; Computer science; Artificial intelligence; Animal science","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":[0.0000872032,0.0001644489,0.0001084415,0.00006023118,0.00005569851,0.00002376501,0.0000750684,0.0001719499,0.0000107409],"category_scores_gemma":[0.00001188356,0.0001810983,0.00003687652,0.00005124242,0.00005812841,0.000002476047,0.00003137672,0.00007834434,0.000003796005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003002198,"about_ca_system_score_gemma":0.00005153053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007788236,"about_ca_topic_score_gemma":0.0002474131,"domain_scores_codex":[0.9990284,0.00005592622,0.0002568061,0.0003880077,0.00007601543,0.0001948773],"domain_scores_gemma":[0.9996999,0.00001797136,0.00007148269,0.0001478924,0.00001898092,0.00004376744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002180209,0.0004847612,0.06328525,0.00001467739,0.00002038735,0.000001251899,0.00006549677,0.6091784,0.3217429,0.0001823799,0.0003560755,0.002488246],"study_design_scores_gemma":[0.001933431,0.0009200563,0.8432639,0.00000832239,0.000006464335,0.000003160508,0.00002110279,0.1126408,0.03993574,0.0000372101,0.001031313,0.0001984804],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957485,0.000202116,0.002447933,0.00003264782,0.00006563447,0.0002138717,0.00003358337,0.00001171684,0.001244034],"genre_scores_gemma":[0.9890177,0.000005006919,0.01041121,0.00009437552,0.0001766875,0.00001447756,0.0001068262,0.00002244179,0.000151251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7799787,"threshold_uncertainty_score":0.7384975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01273474935080859,"score_gpt":0.2595947160961178,"score_spread":0.2468599667453092,"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."}}