{"id":"W3015671526","doi":"","title":"大豆分枝相关CYC/TB1-Like(CYL)基因鉴定及菜用大豆品种的激素表达谱分析","year":2019,"lang":"zh","type":"article","venue":"分子植物育种","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Political 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":[0.0003403695,0.000409432,0.0002288926,0.0004491608,0.001261643,0.001905073,0.000550525,0.000598995,0.01501387],"category_scores_gemma":[0.000504618,0.0002164351,0.0003184683,0.000543551,0.001302261,0.00152424,0.0009637388,0.001041946,0.004141716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002335458,"about_ca_system_score_gemma":0.001366711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003462834,"about_ca_topic_score_gemma":0.001674712,"domain_scores_codex":[0.9998003,0.00001606181,0.000009555514,0.00007124835,0.00004499589,0.00005782901],"domain_scores_gemma":[0.9997588,0.00002091435,0.00006109269,0.00002075892,0.00007068638,0.00006776425],"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":[0.0008132532,0.00009032386,0.007272193,0.0007241621,0.0000708808,0.0009102191,0.001192098,0.002629626,0.7294219,0.1784179,0.009684669,0.06877282],"study_design_scores_gemma":[0.00007624131,0.0002798588,0.01361473,0.0001201813,0.00007639292,0.001654069,0.002393098,0.004426568,0.6876141,0.0234847,0.2661442,0.0001157934],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7219393,0.00911602,0.04589095,0.005074112,0.0009912035,0.0002388581,0.002253817,0.0007610446,0.2137347],"genre_scores_gemma":[0.942884,0.001753128,0.007879834,0.0006529936,0.00006756447,0.00008351966,0.001009492,0.0001044353,0.04556506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01501387,"threshold_uncertainty_score":0.05022639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005955948152888687,"score_gpt":0.1900192797411767,"score_spread":0.1840633315882881,"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."}}