{"id":"W650876585","doi":"","title":"一个水稻雄配子不育基因MGA1（t）的遗传及表达特征分析","year":2011,"lang":"zh","type":"article","venue":"分子植物育种","topic":"Plant tissue culture and regeneration","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"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":[0.0004812082,0.0006302546,0.0005149299,0.0009364425,0.001186602,0.001331229,0.0005569344,0.0009009715,0.004824046],"category_scores_gemma":[0.0006458591,0.0005434551,0.0007619413,0.0009421509,0.0009937343,0.001598565,0.0005206853,0.001423217,0.001864017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001486351,"about_ca_system_score_gemma":0.001282616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002278636,"about_ca_topic_score_gemma":0.00241576,"domain_scores_codex":[0.999249,0.00009017841,0.00004698577,0.0003157755,0.0001982016,0.0000998719],"domain_scores_gemma":[0.9996152,0.00008541049,0.00008857863,0.00003568904,0.0001066902,0.00006845544],"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":[0.0002908783,0.00006764081,0.00427704,0.0003616985,0.00004380116,0.0002877125,0.0005421232,0.0007946451,0.9671174,0.005879034,0.0007766185,0.01956144],"study_design_scores_gemma":[0.00007835619,0.000270078,0.0164796,0.00005003847,0.000153604,0.0007722697,0.0007613815,0.004200206,0.9359123,0.005335144,0.03591758,0.00006945782],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7684225,0.007797755,0.1599719,0.00175428,0.0005521208,0.0006202025,0.002674368,0.002142134,0.05606475],"genre_scores_gemma":[0.9011073,0.002739899,0.06127113,0.0005567878,0.00009346185,0.0004656468,0.002920845,0.000341419,0.0305035],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004824046,"threshold_uncertainty_score":0.01613802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02398312056628726,"score_gpt":0.2257159225545055,"score_spread":0.2017328019882182,"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."}}