Bibliographic record
Abstract
为探讨中国苯丙酮尿症(PKU)人群中苯丙氨酸羟化酶(PAH)基因外显子7的突变特征,对147例PKU患儿的294个PAH基因外显子7以及两侧部分内含子序列,应用PCR-单链构象多态性(SSCP)分析及基因序列分析的方法进行了筛查和确定.共发现13种突变基因:G239D、R241C、R241fs、R243Q、G247S、G247V、R252Q、L255S、R261Q、M276K、E280G、P281L、Ivs7+2T>A,其中7 种突变基因在中国PKU人群首次发现;G239D 、R241fs 、G247S 、E280G、L255S、R261Q、P281L,前4种在国际上尚未见到报道,并已提交到国际PAH突变数据库(www.pahdb.mcgill.ca).突变基因的总频率为30.61%(90 /294).突变涉及了错义、缺失、移码和剪接位点4种突变类型.结果明确了PAH基因外显子7的突变种类和分布等特征,表明外显子7是中国人PAH基因突变的热点区域.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.011 |
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".