{"id":"W2900534476","doi":"10.1126/sciadv.aav0536","title":"Worldwide phylogeography and history of wheat genetic diversity","year":2019,"lang":"en","type":"article","venue":"Science Advances","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":210,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut National de la Recherche Agronomique; Conseil Régional d'Auvergne; Ministère de l'Enseignement Supérieur, de la Recherche, de la Science et de la Technologie; Murdoch University; Agence Nationale de la Recherche; Montana State University","keywords":"Phylogeography; Genetic diversity; Diversity (politics); Evolutionary biology; Biology; Relation (database); Geography; Ecology; Phylogenetics; Genetics; Demography; Anthropology; Gene; Population; Computer science; Sociology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000816761,0.0001714956,0.0002521875,0.002293194,0.0003046859,0.0007390163,0.0001940641,0.0002578217,0.001701834],"category_scores_gemma":[0.001137041,0.0001291589,0.0002846561,0.002162746,0.0005787456,0.0005435365,0.000666399,0.0003314012,0.0002306219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002897432,"about_ca_system_score_gemma":0.000130824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003139406,"about_ca_topic_score_gemma":0.004239652,"domain_scores_codex":[0.9996312,0.0001067759,0.00002070706,0.0001615346,0.00003183777,0.0000479251],"domain_scores_gemma":[0.9992576,0.0002607635,0.0001897278,0.00009852545,0.0001014815,0.00009186323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002192747,0.00002361182,0.9534706,0.0000492687,0.0003240079,0.0002258338,0.001494047,0.0009341316,0.01506569,0.0008403293,0.0001628691,0.02719029],"study_design_scores_gemma":[0.000002692148,0.00002778371,0.9983644,0.000009730608,0.00002196083,0.0001400563,0.0002518058,0.0002521307,0.0001815238,0.000163018,0.0005792386,0.00000569667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997956,0.0005073861,0.0003460828,0.00004365379,0.000001507036,0.000002282092,0.0001881589,0.000005635668,0.0009491703],"genre_scores_gemma":[0.9989731,0.0002794196,0.0001648167,0.00001020442,0.000003714432,0.000002317524,0.0004248657,0.000003749263,0.0001377501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003139406,"threshold_uncertainty_score":0.006242275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076496861039561,"score_gpt":0.1987344090786234,"score_spread":0.1879694404682278,"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."}}