{"id":"W2089675842","doi":"10.1007/s00122-013-2096-7","title":"Using the candidate gene approach for detecting genes underlying seed oil concentration and yield in soybean","year":2013,"lang":"en","type":"article","venue":"Theoretical and Applied Genetics","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"University of Guelph","keywords":"Biology; Gene; Candidate gene; Indel; Population; Quantitative trait locus; Genetics; Genotype; Single-nucleotide polymorphism","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001803123,0.0001120007,0.0001104893,0.000004098003,0.0002447768,0.0001136311,0.00007521678,0.00007726299,0.0000174245],"category_scores_gemma":[0.00001529886,0.00004424519,0.0000185687,0.00009577083,0.0002036464,0.00001874683,0.00004702745,0.00006884948,4.365981e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007592614,"about_ca_system_score_gemma":0.000003943347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004601257,"about_ca_topic_score_gemma":0.0000212286,"domain_scores_codex":[0.9992793,0.0000259941,0.0001655971,0.0002208173,0.00008451832,0.0002237268],"domain_scores_gemma":[0.9996458,0.000180799,0.00004493271,0.00004026223,0.00002819661,0.00005996678],"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":[0.00001597855,0.00001594063,0.001935103,0.00001016105,0.000005491477,5.136469e-8,0.0001931627,0.0001243975,0.8800092,0.01444071,0.000001261686,0.1032486],"study_design_scores_gemma":[0.001252264,0.0003560416,0.1218645,0.00004575004,0.0001049431,0.00002165601,0.009069365,0.355436,0.3935458,0.1172268,0.0001153941,0.0009614528],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966924,0.0003118126,0.002043646,0.0002289084,0.0000171432,0.0003009439,0.000005193761,0.00001264667,0.0003873337],"genre_scores_gemma":[0.9959694,0.0001126785,0.003578759,0.0001696609,0.00009782791,0.00004671696,0.00001538758,0.000001989085,0.000007591419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4864633,"threshold_uncertainty_score":0.188265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04267994562577376,"score_gpt":0.2418149425011352,"score_spread":0.1991349968753615,"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."}}