{"id":"W2890335186","doi":"","title":"水稻金属硫蛋白基因（MT2bL）启动子的克隆与表达分析","year":2017,"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":"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":[0.0005276217,0.0003514279,0.0001954414,0.0007877361,0.001530497,0.003187158,0.0005338719,0.0008951506,0.01969959],"category_scores_gemma":[0.00110079,0.0001768979,0.0001720053,0.0008841217,0.001242978,0.00236715,0.0006493627,0.0007152345,0.005114843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0021333,"about_ca_system_score_gemma":0.0009465453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00375348,"about_ca_topic_score_gemma":0.002968193,"domain_scores_codex":[0.9996696,0.0000484071,0.00001108381,0.00007616711,0.00012068,0.00007404566],"domain_scores_gemma":[0.9995033,0.00006974809,0.00009574671,0.00003232643,0.0002286252,0.00007024379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008660374,0.0002702662,0.02791842,0.001057436,0.0001281158,0.00144943,0.005364055,0.003585735,0.3638757,0.4025358,0.02580688,0.1671421],"study_design_scores_gemma":[0.0001253494,0.0005761768,0.07196753,0.0003468186,0.000191371,0.002542604,0.01466499,0.01224235,0.2239018,0.1917001,0.4815279,0.0002130206],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5271748,0.008552175,0.02840491,0.0129026,0.0008344795,0.0001012589,0.001310075,0.0004870673,0.4202327],"genre_scores_gemma":[0.9405359,0.0009564359,0.00383118,0.0006701684,0.0001181338,0.00004688481,0.0003085292,0.00004866855,0.05348402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01969959,"threshold_uncertainty_score":0.06590164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01525015548171334,"score_gpt":0.2327890850940545,"score_spread":0.2175389296123411,"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."}}