{"id":"W2118440292","doi":"10.3168/jds.s0022-0302(02)74316-6","title":"Strategies for Continual Application of Marker-Assisted Selection in an Open Nucleus Population","year":2002,"lang":"en","type":"article","venue":"Journal of Dairy Science","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Quantitative trait locus; Selection (genetic algorithm); Biology; Genetics; Marker-assisted selection; Population; Locus (genetics); Allele; Chromosome; Gene; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001419471,0.0002789712,0.0004300856,0.0002453281,0.0002637302,0.000489448,0.001204501,0.0003486039,0.0009865175],"category_scores_gemma":[0.001946778,0.0001909349,0.0002965339,0.0001728021,0.0003246165,0.0003338178,0.0005455043,0.0004324855,0.0002275132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007272204,"about_ca_system_score_gemma":0.0006678925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003609546,"about_ca_topic_score_gemma":0.005839183,"domain_scores_codex":[0.9995956,0.00016014,0.00002100319,0.000116408,0.00007925948,0.00002767521],"domain_scores_gemma":[0.999258,0.0003722761,0.0001031505,0.0001181506,0.00007964271,0.00006873079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001306487,0.001503061,0.0586008,0.0001976859,0.0003598192,0.000934717,0.001441211,0.4504116,0.3378415,0.01618684,0.0004574773,0.1307588],"study_design_scores_gemma":[0.0003432163,0.002802194,0.02118403,0.0000268059,0.0002679185,0.0003506638,0.0003183212,0.9279395,0.03769911,0.003536178,0.005432239,0.00009989783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8676694,0.00006443925,0.1306517,0.00002792633,0.00001289191,0.0002058541,0.00004994079,0.0002330084,0.001084706],"genre_scores_gemma":[0.900197,0.00006589235,0.09725747,0.0000302228,0.000004324114,0.0004381031,0.0001350078,0.00004304798,0.001829018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003609546,"threshold_uncertainty_score":0.007506967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02953230944033288,"score_gpt":0.2913365621041225,"score_spread":0.2618042526637896,"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."}}