{"id":"W2899943227","doi":"10.1186/s12863-018-0687-7","title":"Exploring the genetic basis of gene transcript abundance and metabolite levels in loblolly pine (Pinus taeda L.) using association mapping and network construction","year":2018,"lang":"en","type":"article","venue":"BMC Genetics","topic":"Plant Gene Expression Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"U.S. Department of Agriculture; National Institute of Food and Agriculture; National Science Foundation","keywords":"Biology; Single-nucleotide polymorphism; Gene; Genetics; Loblolly pine; Phenotype; Association mapping; Genetic variation; Candidate gene; Genetic association; Computational biology; Evolutionary biology; Genotype; Pinus <genus>; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003737451,0.0001610221,0.0002397521,0.00007615964,0.0001181051,0.00003179656,0.0001212887,0.000102737,0.000004482155],"category_scores_gemma":[0.00007619913,0.0001458657,0.00005516769,0.0002674866,0.0001332565,0.000008606512,0.00007243223,0.00007295258,4.888361e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002304291,"about_ca_system_score_gemma":0.00006105542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003458613,"about_ca_topic_score_gemma":0.0002227465,"domain_scores_codex":[0.9986854,0.0001699318,0.0003739437,0.0003329127,0.0001716128,0.0002661771],"domain_scores_gemma":[0.9993219,0.00002566013,0.0002186201,0.0002553049,0.0001204568,0.00005810951],"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":[0.00002506802,0.00001012786,0.08827854,0.00002256294,0.00005908518,5.573718e-7,0.0002022665,0.002277788,0.9059681,0.00000727966,0.00005620793,0.003092451],"study_design_scores_gemma":[0.0008426897,0.00007869153,0.3961393,0.00006161071,0.0001659413,0.00004451787,0.000290981,0.01184247,0.5861148,0.00009973505,0.004010284,0.000308985],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719303,0.004232651,0.02336629,0.00003868201,0.0001911308,0.0001524008,0.0000329174,0.000005280066,0.00005038695],"genre_scores_gemma":[0.941552,0.002075486,0.05583755,0.00007117503,0.0003596581,0.00001074532,0.00001140282,0.00001825566,0.00006366288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3198533,"threshold_uncertainty_score":0.5948231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05553583335536699,"score_gpt":0.2491139248200836,"score_spread":0.1935780914647166,"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."}}