Bibliographic record
Abstract
β-1,3-葡聚糖酶是一种植物病程相关蛋白,在植物抵御病害中有重要作用。本研究以毛竹为实验材料,利用RACE技术,克隆毛竹β-1,3-葡聚糖酶基因的外显子序列,并在β-1,3-葡聚糖酶基因的编码区两端设计引物,以毛竹基因组DNA为模版扩增该基因的内含子序列。序列结果表明,该基因全长1693bp,包含两个外显子和一个内含子,命名为PheGLU（GenBank登录号GU238236）。该基因包含1个996bp的开放阅读框,编码332个氨基酸,相对分子质量为3.541×104Da,其等电点pI为6.389,是一个酸性蛋白且分泌到胞外;其中,该蛋白的二级结构中包含35.15%的α-螺旋,21.82%的β-转角,43.03%的延伸链和无规则卷曲等;三级结构同源建模预测显示,它与大麦β-1,3-葡聚糖酶（PDB number：1ghsA）具有80.4%的同源性;聚类分析显示,该基因序列与已报道的其它植物具有较的高氨基酸序列同源性。本研究为进一步鉴定毛竹β-1,3-葡聚糖酶基因的抗真菌病害能力奠定了基础。
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".