{"id":"W2070462701","doi":"10.1186/1753-6561-5-s7-i6","title":"Gene mapping in white spruce (P. glauca): QTL and association studies integrating population and expression data","year":2011,"lang":"en","type":"article","venue":"BMC Proceedings","topic":"Forest ecology and management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; FPInnovations; University of Alberta; Université Laval","funders":"","keywords":"Quantitative trait locus; Association mapping; Linkage disequilibrium; Biology; Candidate gene; Genetic association; Family-based QTL mapping; Genetics; Genome-wide association study; Gene; Phenotypic trait; Genetic linkage; Computational biology; Expression quantitative trait loci; Population; Genetic architecture; Phenotype; Gene mapping; Locus (genetics); Genotype; Single-nucleotide polymorphism; Chromosome; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005841909,0.0000738137,0.00009275937,0.00003776872,0.000100738,0.00001909695,0.00009653225,0.00005087156,0.00003128899],"category_scores_gemma":[0.0003077319,0.0000647729,0.000004889368,0.00009479152,0.00003514518,0.0005980789,0.0005824952,0.00006856328,0.000006539825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000106101,"about_ca_system_score_gemma":0.000001302408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001636884,"about_ca_topic_score_gemma":0.0005657451,"domain_scores_codex":[0.9993483,0.00000913752,0.0001431665,0.0002702348,0.00009482175,0.0001342972],"domain_scores_gemma":[0.9997684,0.0000231535,0.0001169933,0.00006119078,0.00000670972,0.00002350403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006258433,0.00001259528,0.9940436,0.00002727335,0.000003728811,3.723e-7,0.003010581,8.814636e-7,0.001091335,0.0002707251,0.0008624157,0.0006702699],"study_design_scores_gemma":[0.0001721149,0.00001746855,0.9935199,0.00004348166,0.00000771278,0.000001249318,0.001772594,0.001125701,0.0002859913,0.002821125,0.0001542277,0.00007842478],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976928,0.0000872427,0.0001706279,0.00007360404,0.00005109778,0.0001737165,9.828976e-7,0.00002263076,0.001727261],"genre_scores_gemma":[0.9836452,0.00006825304,0.01593465,0.0000702375,0.00001623187,0.00001558696,0.000005760783,0.000004741333,0.000239346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01576402,"threshold_uncertainty_score":0.2641362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05317632300872377,"score_gpt":0.2582373029431638,"score_spread":0.2050609799344401,"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."}}