{"id":"W3093879470","doi":"10.1038/s41588-020-00722-w","title":"Triticum population sequencing provides insights into wheat adaptation","year":2020,"lang":"en","type":"article","venue":"Nature Genetics","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":410,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Genetics","funders":"Biotechnology and Biological Sciences Research Council; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Biology; Subspecies; Adaptation (eye); Introgression; Aegilops; Genetic diversity; Convergent evolution; Genome; Selection (genetic algorithm); Population; Evolutionary biology; Ploidy; Genetics; Gene; Phylogenetics; Ecology","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":[0.0007850986,0.0004600394,0.0004168725,0.0008228068,0.0004234853,0.0006769165,0.0004173731,0.0007012856,0.002712621],"category_scores_gemma":[0.0007035499,0.0003313838,0.0005654807,0.0008706826,0.0002166831,0.0004629459,0.0006612458,0.001402064,0.0006087973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004329673,"about_ca_system_score_gemma":0.0003957762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001431815,"about_ca_topic_score_gemma":0.005273771,"domain_scores_codex":[0.9997081,0.0000471917,0.00002228426,0.0001361589,0.0000480645,0.00003823199],"domain_scores_gemma":[0.9996879,0.0001110888,0.000054751,0.0000561671,0.00004374632,0.00004645208],"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":[0.0002122393,0.0000721062,0.01322412,0.000127312,0.0001710604,0.0003116594,0.000497888,0.0008717735,0.9423348,0.002756541,0.0008817515,0.03853868],"study_design_scores_gemma":[0.0003360728,0.0006863583,0.7103555,0.0001869778,0.001014544,0.002232311,0.0009679221,0.01870717,0.1563375,0.01067008,0.09837041,0.000135163],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9408767,0.001905147,0.04057952,0.000621638,0.0001803096,0.00009741374,0.004625654,0.0005432431,0.01057046],"genre_scores_gemma":[0.9591104,0.001596321,0.02351679,0.0008902111,0.00006558859,0.0001100689,0.00874053,0.0002486915,0.005721262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002712621,"threshold_uncertainty_score":0.009074569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02865402041247173,"score_gpt":0.2372008332860571,"score_spread":0.2085468128735854,"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."}}