{"id":"W4407225347","doi":"10.1093/forestry/cpaf004","title":"Genome-wide SNP-based relationships improve genetic parameter estimates and genomic prediction of growth traits in a large operational breeding trials of <i>Pinus taeda</i> L.","year":2025,"lang":"en","type":"article","venue":"Forestry An International Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mitel (Canada)","funders":"","keywords":"Biology; Pinus <genus>; SNP; Genome; Genomic selection; Genetics; Computational biology; Evolutionary biology; Single-nucleotide polymorphism; Gene; Genotype; Botany","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":[0.001411825,0.0003567289,0.0002411146,0.0003686494,0.0002331439,0.0003213174,0.0003738421,0.0001698371,0.0004767544],"category_scores_gemma":[0.001361959,0.0001328307,0.0002780291,0.0002845714,0.0001754365,0.0001763983,0.0002708262,0.0002988122,0.00009963477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003689971,"about_ca_system_score_gemma":0.0002335691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00677643,"about_ca_topic_score_gemma":0.01778131,"domain_scores_codex":[0.9994714,0.0002328285,0.0000194097,0.0001872379,0.00006316837,0.00002606719],"domain_scores_gemma":[0.9992092,0.000378922,0.0001765923,0.00007779155,0.00008636052,0.00007106852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000746848,0.000554098,0.6913559,0.0001007567,0.0004528873,0.0004179897,0.0008757343,0.008417772,0.2355666,0.0003194752,0.000366028,0.06082588],"study_design_scores_gemma":[0.00003978868,0.0005292191,0.9649267,0.00001095502,0.0001843968,0.0001537978,0.0001883558,0.02614143,0.006708744,0.0001296263,0.0009709502,0.00001612862],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977665,0.00003728739,0.001860529,0.00001109861,0.000001092853,0.00001400473,0.0001471468,0.0000250717,0.0001373348],"genre_scores_gemma":[0.9959335,0.00001798199,0.003475415,0.00001133318,0.000001258448,0.00002158203,0.0003922094,0.000009584718,0.0001372205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00677643,"threshold_uncertainty_score":0.01347399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0541830998663278,"score_gpt":0.3357318803543293,"score_spread":0.2815487804880015,"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."}}