{"id":"W2744775149","doi":"10.1111/eva.12527","title":"Gene flow in Argentinian sunflowers as revealed by genotyping‐by‐sequencing data","year":2017,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Consejo Nacional de Investigaciones Científicas y Técnicas","keywords":"Introgression; Biology; Domestication; Gene flow; Helianthus; Hybrid; Sunflower; Genotyping; Gene pool; Range (aeronautics); Genetics; Genotype; Evolutionary biology; Gene; Genetic variation; Botany; Genetic diversity; Horticulture; Population","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004899557,0.0002237839,0.000178909,0.0008561148,0.0003376113,0.0004010251,0.0001229089,0.000192581,0.000815744],"category_scores_gemma":[0.0005314383,0.00008742209,0.0001321766,0.0007410863,0.0001770825,0.0001176932,0.0001536534,0.0001670426,0.0001203585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003515415,"about_ca_system_score_gemma":0.0001277651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00771635,"about_ca_topic_score_gemma":0.01086339,"domain_scores_codex":[0.9997295,0.000043484,0.00001762686,0.000119276,0.00005602798,0.0000341239],"domain_scores_gemma":[0.9995364,0.0001086221,0.0001774474,0.00004514794,0.00008851162,0.00004387354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006943571,0.00005564372,0.6589857,0.0001187507,0.0001827517,0.0003873624,0.001582918,0.000871602,0.300524,0.0003519378,0.0003136364,0.03593126],"study_design_scores_gemma":[0.000006953644,0.00003507708,0.9933984,0.000009609224,0.00002729561,0.0001848913,0.0001231966,0.0006993833,0.003585225,0.00006189876,0.001863005,0.000005060123],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979798,0.0001251859,0.0006191991,0.00001874887,0.000002887279,0.000005234338,0.0005407347,0.000009144653,0.0006990155],"genre_scores_gemma":[0.9975632,0.00008936504,0.0009674888,0.00001270478,0.000004247237,0.000008932904,0.001021138,0.000005762459,0.0003269932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00771635,"threshold_uncertainty_score":0.01534289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02218568884769725,"score_gpt":0.2761223580988901,"score_spread":0.2539366692511928,"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."}}