{"id":"W2513543698","doi":"10.1186/s12864-016-3041-3","title":"Characterizing the population structure and genetic diversity of maize breeding germplasm in Southwest China using genome-wide SNP markers","year":2016,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":221,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"National Natural Science Foundation of China; DuPont Pioneer","keywords":"Germplasm; Biology; Genetic diversity; Linkage disequilibrium; Population; Temperate climate; Single-nucleotide polymorphism; Genetics; Evolutionary biology; Ecology; Botany; Genotype; Gene; Demography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001039645,0.0001141036,0.0001261128,0.00004458892,0.0001633373,0.00001790081,0.0001476895,0.0000929423,0.00001102904],"category_scores_gemma":[0.00003147532,0.00008133612,0.00004272052,0.00003916902,0.00005973805,0.000004534008,0.0003247824,0.00004121019,5.519505e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002013161,"about_ca_system_score_gemma":0.00002396995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003026991,"about_ca_topic_score_gemma":0.0001870317,"domain_scores_codex":[0.9993347,0.00003757072,0.0001608482,0.000219223,0.00007300304,0.0001746632],"domain_scores_gemma":[0.9996486,0.00001879931,0.0001197021,0.0001513421,0.00001932018,0.00004221765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004255794,0.000003983666,0.5567111,0.00001450887,0.00001047106,8.121308e-7,0.0001185048,0.00009890171,0.4427395,0.000003709412,0.000003754319,0.0002521676],"study_design_scores_gemma":[0.0003847722,0.00004367148,0.9936739,0.00002053621,0.00002100436,0.00001629292,0.0001597218,0.0000818145,0.00521524,0.00007078127,0.0001870319,0.0001252607],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990041,0.000115568,0.0004876692,0.00004689613,0.00007889053,0.0001149178,0.0001165964,0.000003178638,0.00003217844],"genre_scores_gemma":[0.9983248,0.0001439639,0.001348258,0.00004648108,0.0000736542,4.031964e-7,0.00001728753,0.000007735863,0.00003741565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4375243,"threshold_uncertainty_score":0.3316791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01849124500236812,"score_gpt":0.209220046570402,"score_spread":0.1907288015680339,"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."}}