{"id":"W1971274641","doi":"10.1007/s00122-012-1990-8","title":"Identification of the quantitative trait loci (QTL) underlying water soluble protein content in soybean","year":2012,"lang":"en","type":"article","venue":"Theoretical and Applied Genetics","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Agriculture","funders":"Innovation Scientists and Technicians Troop Construction Projects of Henan Province; Henan Academy of Agricultural Sciences; Chinese Academy of Agricultural Sciences; Chinese Academy of Sciences","keywords":"Quantitative trait locus; Biology; Family-based QTL mapping; Genetics; Population; Trait; Genetic linkage; Inclusive composite interval mapping; Inbred strain; Gene; Gene mapping","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001545137,0.0002444196,0.0002123647,0.0005073296,0.0001249422,0.0002002682,0.0002013623,0.0001868383,0.0005538675],"category_scores_gemma":[0.0001852803,0.0001976577,0.0002631851,0.0003300253,0.0002165052,0.0001314696,0.0001705115,0.0003268387,0.0001062405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003978094,"about_ca_system_score_gemma":0.0002656912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003415484,"about_ca_topic_score_gemma":0.004226266,"domain_scores_codex":[0.9999319,0.000006391441,0.000004915396,0.00002953392,0.00001520311,0.00001199139],"domain_scores_gemma":[0.999854,0.00005049357,0.00003312305,0.000007024026,0.00001576134,0.00003961102],"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":[0.0001390051,0.00001149011,0.002325486,0.00001508514,0.000006146775,0.00002948925,0.00002851705,0.0001190621,0.9962975,0.00008572417,0.000006610856,0.000935891],"study_design_scores_gemma":[0.000116507,0.0004277892,0.5825081,0.00001209779,0.0001146106,0.0005831731,0.000224322,0.008248133,0.4055426,0.0006496788,0.001544022,0.00002887639],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978547,0.00009491449,0.001585028,0.00002441768,0.000002581746,0.000004035934,0.000232636,0.00001595205,0.0001857924],"genre_scores_gemma":[0.9972352,0.00005930987,0.00159018,0.0000143639,0.000001875736,0.000005244253,0.0005125284,0.00001044768,0.0005707058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003415484,"threshold_uncertainty_score":0.006791234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05131338988696688,"score_gpt":0.2478315977167976,"score_spread":0.1965182078298307,"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."}}