{"id":"W2900994740","doi":"10.3389/fpls.2018.01693","title":"Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding","year":2018,"lang":"en","type":"review","venue":"Frontiers in Plant Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":224,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Fundação de Apoio à Pesquisa do Distrito Federal; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Genome Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Genome British Columbia","keywords":"Genomics; Biology; Tree breeding; Quantitative genetics; Tree (set theory); Evolutionary biology; Computational biology; Genetics; Biotechnology; Genome; Genetic variation; Ecology; Gene; Woody plant; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004554199,0.0003364383,0.0005957733,0.0002627491,0.0001511019,0.00008553531,0.0008157173,0.0002312118,0.000002331547],"category_scores_gemma":[0.0001051394,0.0003019373,0.00007381242,0.0003840876,0.0006832866,0.000006974532,0.0003979229,0.0001594271,0.00001061365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005982088,"about_ca_system_score_gemma":0.000495176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005739005,"about_ca_topic_score_gemma":0.00005177724,"domain_scores_codex":[0.9980076,0.00005099798,0.0003887024,0.000858167,0.0002006315,0.0004938795],"domain_scores_gemma":[0.9991658,0.00002238585,0.0001649297,0.0003697637,0.00006387115,0.000213266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003749926,0.0001848238,0.005091664,0.004956644,0.0003534983,0.00002073073,0.001722211,0.000394047,0.001808975,0.005460958,0.08000456,0.8996269],"study_design_scores_gemma":[0.0001925191,0.0009225511,0.0008185412,0.0009200519,0.00008337585,0.0000438808,0.0001252756,0.0001601788,0.000169137,0.0003847095,0.9955823,0.000597431],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.007089269,0.9754415,0.0141052,0.00001038569,0.001809281,0.0006648487,0.0002552495,0.000007735039,0.0006164983],"genre_scores_gemma":[0.0003011624,0.8620391,0.1370089,0.0000816459,0.0002123178,0.0000367643,0.00008533603,0.00003019559,0.0002045295],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9155778,"threshold_uncertainty_score":0.9999433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04172533403371249,"score_gpt":0.2985868360223824,"score_spread":0.2568615019886699,"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."}}