{"id":"W4220926454","doi":"10.5376/mgg.2022.13.0002","title":"Genetic Diversity Analysis of Maize in Baoshan Yunnan by SSR Markers","year":2022,"lang":"en","type":"article","venue":"Maize Genomics and Genetics","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genetic diversity; Genetic similarity; Allele; Similarity (geometry); Biology; Genetic distance; Diversity index; Veterinary medicine; Statistics; Biotechnology; Genetic variation; Mathematics; Genetics; Demography; Population; Ecology; Sociology; Gene; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0004305834,0.0002392526,0.0003138495,0.002029168,0.0009057575,0.0003611109,0.000170844,0.0001384594,0.0002902021],"category_scores_gemma":[0.0002499975,0.0001823967,0.0003475694,0.002404436,0.0002349973,0.0001745998,0.0003252693,0.000198122,0.0000429867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006557357,"about_ca_system_score_gemma":0.0006353635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01701468,"about_ca_topic_score_gemma":0.02492662,"domain_scores_codex":[0.9997267,0.00003175978,0.00003020161,0.00009878514,0.00007150225,0.00004104521],"domain_scores_gemma":[0.999867,0.00002152843,0.00003703701,0.000007324574,0.00003593676,0.00003123928],"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":[0.0006554869,0.0001344122,0.4352263,0.0001876619,0.000276722,0.0007457166,0.005557971,0.00106621,0.5230772,0.0006342155,0.0001103185,0.03232774],"study_design_scores_gemma":[0.00002306664,0.0001113776,0.9907703,0.00001247551,0.00006793267,0.0002541771,0.00107687,0.001120622,0.005192168,0.000163604,0.001181103,0.00002630507],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994575,0.00007859102,0.0002003802,0.000008397861,8.236135e-7,0.00000642418,0.0000924458,0.000002232145,0.0001531498],"genre_scores_gemma":[0.9982001,0.0001158916,0.0009810471,0.0000081301,0.000001989822,0.00001786216,0.0003904832,0.00000267649,0.0002818081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01701468,"threshold_uncertainty_score":0.0338313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006582095341075408,"score_gpt":0.1880249265997687,"score_spread":0.1814428312586933,"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."}}