{"id":"W2187912871","doi":"10.1111/nph.13762","title":"Genetic architecture of wood properties based on association analysis and co‐expression networks in white spruce","year":2015,"lang":"en","type":"article","venue":"New Phytologist","topic":"Forest ecology and management","field":"Environmental Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Genomics; Natural Resources Canada; Canadian Forest Service; Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies; Genome Canada","keywords":"Biology; Genetic architecture; Genetic association; Trait; Single-nucleotide polymorphism; Association mapping; Gene; Quantitative trait locus; Computational biology; Xylem; Population; Genetics; Genome-wide association study; Expression quantitative trait loci; Candidate gene; Evolutionary biology; White (mutation); Botany; Genotype; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000759228,0.0001855666,0.0002634379,0.001163283,0.0002758063,0.0005738047,0.0002762717,0.000196655,0.0005991894],"category_scores_gemma":[0.00141995,0.0001884843,0.0004544017,0.0009029068,0.0004556324,0.0003233711,0.0003846575,0.0003136293,0.00009481393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002738107,"about_ca_system_score_gemma":0.0002428146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003800699,"about_ca_topic_score_gemma":0.006190317,"domain_scores_codex":[0.9994772,0.0001499123,0.00002350062,0.0002600233,0.00004794153,0.00004153328],"domain_scores_gemma":[0.9987148,0.0006932704,0.0003088168,0.0001244505,0.00008456175,0.00007416376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005816901,0.0001126352,0.8001251,0.0001016843,0.000782384,0.0003873418,0.0006842053,0.02266142,0.1375406,0.002719198,0.0001864908,0.03411723],"study_design_scores_gemma":[0.00001415679,0.00006373534,0.9034878,0.00001159682,0.0002230601,0.0002537221,0.000195478,0.08760785,0.004016592,0.003686435,0.0004171004,0.00002242304],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891399,0.0001807481,0.01019023,0.00002153606,0.000001826126,0.000006730949,0.0001075329,0.00003094223,0.0003206274],"genre_scores_gemma":[0.9968984,0.00005690907,0.002727049,0.000005850341,0.000002270981,0.000007309321,0.0001508869,0.000006044224,0.0001453124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003800699,"threshold_uncertainty_score":0.007557154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01165755917030892,"score_gpt":0.21713291904438,"score_spread":0.2054753598740711,"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."}}