{"id":"W2883431362","doi":"","title":"GENETIC DIVERSITY OF WHEAT CULTIVARS ESTIMATED BY SSR MARKERS","year":2008,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Microsatellite; Genetic diversity; Biology; Selection (genetic algorithm); Genetic marker; Cultivar; RAPD; Biotechnology; Genetic variation; Genetics; Evolutionary biology; Allele; Agronomy; Population; Gene; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005118801,0.0002190658,0.0003117482,0.002141075,0.0002648955,0.0005102781,0.0001875637,0.0002287305,0.0004752068],"category_scores_gemma":[0.0007038876,0.0001680799,0.0002158751,0.001473372,0.0002070969,0.0001678961,0.0002375861,0.000224017,0.0002242414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002449004,"about_ca_system_score_gemma":0.0001782319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001434852,"about_ca_topic_score_gemma":0.001937935,"domain_scores_codex":[0.9993665,0.00009278802,0.00008042043,0.0002412032,0.0001610001,0.00005824017],"domain_scores_gemma":[0.9995918,0.00007259482,0.0001603717,0.00003801794,0.00008997898,0.00004727986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006679631,0.0001884177,0.604942,0.0001082207,0.0001827738,0.0001724185,0.00065273,0.000607658,0.3636333,0.0001459694,0.000109745,0.02858881],"study_design_scores_gemma":[0.000008566949,0.0002546643,0.9898493,0.00001031459,0.00004235525,0.00029565,0.0001472002,0.0004052466,0.008313534,0.00005724012,0.0006072936,0.000008532638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979528,0.0002366509,0.0008095324,0.000004546017,0.000002704087,0.0000156069,0.0004543604,0.000009320372,0.0005144553],"genre_scores_gemma":[0.9944718,0.0001991761,0.00301878,0.000006691625,0.000003313932,0.00002045362,0.001964075,0.000004760856,0.000311016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002141075,"threshold_uncertainty_score":0.002853036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2170329675252497,"score_gpt":0.4473970540893782,"score_spread":0.2303640865641285,"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."}}