{"id":"W2994955049","doi":"10.1038/s41598-019-53620-5","title":"Mapping dynamic QTL dissects the genetic architecture of grain size and grain filling rate at different grain-filling stages in barley","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"Earmarked Fund for China Agriculture Research System","keywords":"Quantitative trait locus; Genetic architecture; Doubled haploidy; Biology; Population; Grain size; Selection (genetic algorithm); Locus (genetics); Candidate gene; Hordeum vulgare; Agronomy; Gene; Genetics; Materials science; Poaceae; Computer science; Artificial intelligence","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":[0.0001787244,0.000214872,0.0002836055,0.0004882172,0.0001485482,0.0002045876,0.0002084209,0.0001302996,0.0006661783],"category_scores_gemma":[0.0001807557,0.0002237323,0.0002816716,0.0004643615,0.0002177522,0.0001294747,0.0002030869,0.0002347329,0.0001604968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003202528,"about_ca_system_score_gemma":0.0002439275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002901476,"about_ca_topic_score_gemma":0.003264491,"domain_scores_codex":[0.999884,0.000007029847,0.000006605466,0.00006392498,0.0000193481,0.00001911999],"domain_scores_gemma":[0.9998724,0.00002768803,0.0000409265,0.00001445416,0.00001364635,0.00003097176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000361955,0.00003479823,0.01194457,0.00002997341,0.00002065324,0.0001055424,0.0001421009,0.0004420354,0.9797156,0.0001600271,0.0000290696,0.00701371],"study_design_scores_gemma":[0.00006660308,0.0002387114,0.8988362,0.000009041289,0.00009709138,0.0005501676,0.0001265781,0.004206481,0.09394003,0.0004129869,0.00147709,0.00003907295],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928777,0.0001773566,0.006227141,0.00001024261,0.000004105198,0.00001083955,0.0004097427,0.00005392912,0.0002288562],"genre_scores_gemma":[0.9945747,0.000110692,0.003791797,0.00001002532,0.000003717855,0.00001807221,0.0005786507,0.00004413852,0.0008682829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002901476,"threshold_uncertainty_score":0.005769193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009632953332950993,"score_gpt":0.2075977449807693,"score_spread":0.1979647916478183,"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."}}