{"id":"W2107100889","doi":"10.1155/2013/613062","title":"Genetic Diversity Analysis of Sugarcane Parents in Chinese Breeding Programmes Using gSSR Markers","year":2013,"lang":"en","type":"article","venue":"The Scientific World JOURNAL","topic":"Sugarcane Cultivation and Processing","field":"Agricultural and Biological Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"National High-tech Research and Development Program; Fujian Agriculture and Forestry University","keywords":"Genetic diversity; Biology; Microsatellite; Biotechnology; Cultivar; Plant breeding; Crop; Allele; Selection (genetic algorithm); Principal component analysis; Genetic variation; Genetic marker; Breeding program; Genotype; Agronomy; Genetics; Gene; Population; Medicine; Statistics","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":[0.0006016487,0.0002781261,0.000251512,0.00135047,0.0005051515,0.0003377414,0.0002485673,0.0001605648,0.0004961549],"category_scores_gemma":[0.0005199902,0.0001436099,0.0003137355,0.001540883,0.0002512215,0.0001307322,0.0002546068,0.0001793302,0.00008321767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004714664,"about_ca_system_score_gemma":0.0006278579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01072415,"about_ca_topic_score_gemma":0.01520781,"domain_scores_codex":[0.9995605,0.0000492025,0.00003486698,0.0001588693,0.000125971,0.0000704609],"domain_scores_gemma":[0.9997801,0.00004604681,0.00004190611,0.000027973,0.00006244457,0.00004141549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004658485,0.0001606823,0.3315001,0.0001040886,0.0002472231,0.001273688,0.004571413,0.0008945887,0.582935,0.0006262881,0.0002114954,0.07700951],"study_design_scores_gemma":[0.0000165296,0.0001561873,0.9740474,0.00001079198,0.0001479781,0.0003404242,0.0005698174,0.001291526,0.02185803,0.00008144253,0.001458642,0.00002129852],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990694,0.00003453817,0.0004408924,0.000005388697,0.000001611135,0.00001367243,0.00008802715,0.000007801344,0.000338543],"genre_scores_gemma":[0.996958,0.00009513048,0.001515413,0.00001164121,0.000002420304,0.00002273608,0.0007713458,0.00001037041,0.0006130504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01072415,"threshold_uncertainty_score":0.02132344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03683774190153909,"score_gpt":0.254952654791028,"score_spread":0.2181149128894889,"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."}}