{"id":"W101244573","doi":"","title":"利用农杆菌介导法将柠檬酸合成酶基因（CS）导入籼稻品种明恢86","year":2006,"lang":"zh","type":"article","venue":"分子植物育种","topic":"Phytase and its Applications","field":"Agricultural and Biological Sciences","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001747658,0.0002356925,0.000228106,0.00001731774,0.0004385451,0.0001504427,0.0003920409,0.000181468,0.002363409],"category_scores_gemma":[0.0000127257,0.0001038744,0.0001774941,0.0005514714,0.0001345062,0.0001526951,0.0000994874,0.0001757161,0.00272354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003457484,"about_ca_system_score_gemma":0.00001881717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00256889,"about_ca_topic_score_gemma":0.0007653243,"domain_scores_codex":[0.9983685,0.00006939412,0.0003327974,0.0004666492,0.0002471849,0.0005155009],"domain_scores_gemma":[0.9994034,0.0001000695,0.0001232447,0.0001642897,0.0000696188,0.0001393975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001510874,0.001059269,0.01284899,0.00002512036,0.00004060976,0.00001728795,0.00006507227,0.00001754406,0.2729148,0.2115144,0.3812228,0.120259],"study_design_scores_gemma":[0.0001912829,0.0001317607,0.3723303,0.00002985871,0.00004540331,0.000009885893,0.0001372831,0.00004228351,0.003012845,0.05330163,0.5703219,0.0004455654],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4651174,0.002964107,0.00002057799,0.009641655,0.0004232861,0.0003816435,0.0003533078,0.0001669061,0.5209312],"genre_scores_gemma":[0.9763508,0.0001670453,0.0000749541,0.0005375635,0.002760682,0.0000333369,0.0002583373,0.000002762263,0.01981456],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5112334,"threshold_uncertainty_score":0.9985486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01539249016369935,"score_gpt":0.2111627555240267,"score_spread":0.1957702653603274,"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."}}