{"id":"W2946831748","doi":"10.1111/eva.12823","title":"Multi‐trait genomic selection for weevil resistance, growth, and wood quality in Norway spruce","year":2019,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval; Gouvernement du Québec; Natural Resources Canada","funders":"Genome Canada","keywords":"Biology; Weevil; Resistance (ecology); Selection (genetic algorithm); Trait; Biotechnology; Quality (philosophy); Ecology; Agronomy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001026213,0.0004951981,0.0002625027,0.0003588849,0.0002190106,0.0003821855,0.0002579063,0.0001282748,0.0002567926],"category_scores_gemma":[0.0004196979,0.0001252091,0.0003696858,0.0002150273,0.0001855255,0.0001092524,0.0002274635,0.0002493827,0.00003547649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007316428,"about_ca_system_score_gemma":0.0004743336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02563684,"about_ca_topic_score_gemma":0.061134,"domain_scores_codex":[0.9997694,0.0000813019,0.00001293694,0.00007384015,0.00003388101,0.00002868733],"domain_scores_gemma":[0.9996425,0.0001764969,0.00005632541,0.0000242905,0.00004317606,0.00005726137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007421461,0.0004493692,0.4149885,0.00007256671,0.0006214053,0.0003824491,0.0004379165,0.06238172,0.4852878,0.0007346297,0.0002219269,0.03367954],"study_design_scores_gemma":[0.00004255107,0.0006146244,0.792328,0.00001516534,0.0002135657,0.0001800737,0.0002418913,0.187755,0.01741524,0.000358683,0.0008005738,0.00003461054],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976621,0.00002582087,0.002115945,0.000004765533,0.000001670811,0.000004107621,0.0000604077,0.00002479302,0.0001004725],"genre_scores_gemma":[0.9967986,0.00002141779,0.002788812,0.000008472325,0.0000011442,0.000006575658,0.0001710557,0.0000108944,0.0001929506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02563684,"threshold_uncertainty_score":0.05097526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008324996034594662,"score_gpt":0.2380104459214116,"score_spread":0.229685449886817,"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."}}