{"id":"W4382776658","doi":"10.1111/pbi.14104","title":"Deciphering genetic basis of developmental and agronomic traits by integrating high‐throughput optical phenotyping and genome‐wide association studies in wheat","year":2023,"lang":"en","type":"article","venue":"Plant Biotechnology Journal","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Saskatchewan Research Council (Canada)","funders":"National Key Research and Development Program of China; Huazhong Agricultural University; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Hubei Province; National Natural Science Foundation of China","keywords":"Biology; Quantitative trait locus; Genetic architecture; Genome-wide association study; Trait; Association mapping; Genetic association; Genetics; Candidate gene; Genome; Selection (genetic algorithm); Phenotype; Population; Gene; Genotype; Single-nucleotide polymorphism","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":[0.000507245,0.0003177771,0.0003833064,0.0006420412,0.0002464553,0.0004889514,0.0002344378,0.0002513524,0.0003584736],"category_scores_gemma":[0.0003247726,0.0001971726,0.0004610874,0.001010181,0.000168318,0.0002710331,0.0004275112,0.0004063261,0.0001158427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002260293,"about_ca_system_score_gemma":0.0002060349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00218269,"about_ca_topic_score_gemma":0.003655094,"domain_scores_codex":[0.9997666,0.00002991093,0.00001558851,0.0001072887,0.00004616623,0.00003443929],"domain_scores_gemma":[0.9997497,0.00006985063,0.0000950021,0.00003298541,0.00002770676,0.00002483639],"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":[0.0002252225,0.00009552898,0.1115005,0.000200526,0.0002337423,0.0002289216,0.000168352,0.002045051,0.8470668,0.0005047554,0.0001816355,0.03754909],"study_design_scores_gemma":[0.00002194372,0.0001812424,0.9463883,0.00001756627,0.000280984,0.0004018467,0.0001224923,0.01409619,0.034835,0.0007794995,0.002843454,0.00003146144],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969703,0.001434835,0.02665982,0.00007281992,0.00001222498,0.00002606666,0.001418157,0.000116155,0.0005568314],"genre_scores_gemma":[0.9784007,0.001050614,0.01793505,0.00008846533,0.00001097434,0.0000340641,0.001878178,0.00002616539,0.0005756735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00218269,"threshold_uncertainty_score":0.004339933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02309757258730538,"score_gpt":0.2220692073962718,"score_spread":0.1989716348089664,"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."}}