{"id":"W4407402262","doi":"10.1038/s41437-025-00747-z","title":"Revealing stable SNPs and genomic prediction insights across environments enhance breeding strategies of productivity, defense, and climate-adaptability traits in white spruce","year":2025,"lang":"en","type":"article","venue":"Heredity","topic":"Forest ecology and management","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Alberta; Natural Resources Canada; University of British Columbia; Canadian Forest Service","funders":"Genome Alberta; Alberta Innovates; Genome British Columbia; Genome Canada","keywords":"Adaptability; Biology; White (mutation); Productivity; Climate change; Evolutionary biology; Single-nucleotide polymorphism; Biotechnology; Ecology; Genetics; Gene; Genotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005811109,0.0001186396,0.0001882947,0.0000283084,0.000134502,0.00002388112,0.00008436313,0.00008220084,0.00003674813],"category_scores_gemma":[0.00002496212,0.0001204234,0.00001479155,0.0001318753,0.0003788631,0.000460172,0.0003855593,0.0001342786,0.000003261365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001609244,"about_ca_system_score_gemma":0.00001206229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002298381,"about_ca_topic_score_gemma":0.005471624,"domain_scores_codex":[0.9988837,0.00006761308,0.0002480465,0.0004334118,0.0001120335,0.0002552314],"domain_scores_gemma":[0.9996892,0.00003537595,0.00008431609,0.0001518045,0.00000310581,0.00003618115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001046128,0.0001963791,0.9619052,0.0002271857,0.00001670214,0.000003110264,0.002351301,0.00252393,0.02974356,0.0007612223,0.0001417855,0.002025024],"study_design_scores_gemma":[0.00025851,0.00005937944,0.9934396,0.00003058875,0.00001108369,0.000001220388,0.0008684602,0.0004872684,0.00147415,0.002797787,0.000493249,0.00007870315],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960778,0.0001682622,0.0003535323,0.00005557077,0.0001709634,0.0003683432,0.00002069019,0.0000157151,0.002769146],"genre_scores_gemma":[0.999212,0.0001757875,0.000329342,0.00001185137,0.00001584289,0.00002292707,0.000003187499,0.000004332958,0.0002247799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03153441,"threshold_uncertainty_score":0.4910722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009627957166023052,"score_gpt":0.2331374579827117,"score_spread":0.2235095008166887,"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."}}