{"id":"W3121038326","doi":"10.1007/s10722-020-01071-7","title":"Genetic variation among Iranian Medicago polymorpha L. populations based on SSR markers","year":2021,"lang":"en","type":"article","venue":"Genetic Resources and Crop Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Biology; Genetic diversity; Mantel test; Genetic variation; Genetic distance; Isolation by distance; Genetic structure; Population; Genetic variability; Botany; Genetics; 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":[0.0001004969,0.000188384,0.00013935,0.00008407008,0.0003167687,0.00007015943,0.0001173931,0.0002357369,0.0001958037],"category_scores_gemma":[0.00006677238,0.0001965339,0.00009014148,0.0001805454,0.0001138995,0.000004769776,0.00007178825,0.00009550213,0.00001032925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002524916,"about_ca_system_score_gemma":0.00007475218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001836436,"about_ca_topic_score_gemma":0.0001974489,"domain_scores_codex":[0.998553,0.0001608551,0.0002510036,0.000484832,0.0002974767,0.0002528422],"domain_scores_gemma":[0.9992295,0.00001056713,0.000118459,0.0003784888,0.0001063613,0.0001566299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003443452,0.000158482,0.8550893,0.00008714642,0.0001320996,0.00003386903,0.000556107,0.05931727,0.06215339,0.0002707764,0.005040309,0.01681692],"study_design_scores_gemma":[0.0007012436,0.0001584495,0.9793724,0.00002130917,0.00006760222,0.00002186932,0.0001209853,0.007232603,0.0005123535,0.0002493958,0.01131481,0.0002270208],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784973,0.001278825,0.01867334,0.0002931308,0.0002535301,0.0001623824,0.00003736807,0.00001893168,0.0007851687],"genre_scores_gemma":[0.993494,0.00007969446,0.004892395,0.0003584795,0.0002793781,0.000008539503,0.0001620395,0.00001917348,0.0007062589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1242831,"threshold_uncertainty_score":0.8014419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00767822081379007,"score_gpt":0.2075549416373899,"score_spread":0.1998767208235999,"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."}}