Bibliographic record
Abstract
目的：探讨人类CYP17基因启动子5＇上游-34碱基处T→C突变与复发性流产的关系,以期为预防和治疗该病易感人群提供新思路。方法：采用聚合酶链式反应-限制性片段长度多态性（PCR-RFLP）方法,针对CYP17基因启动子5＇上游-34碱基处的多态性,检测96例患有原因不明复发性流产患者（病例组）和102例有生育史的健康女性（对照组）,并用非变性聚丙烯酰胺凝胶电泳和银染法进一步验证,且采用测序方法证实实验结果。结果：病例组和对照组CYP17基因启动子5＇上游-34碱基处T和C的分布差异有统计学意义（χ2=8.188,P〈0.05）,CYP17基因各基因型分布差异有统计学意义（χ2=10.096,P〈0.05）。杂合突变（T/C）基因型和纯合突变（C/C）基因型患复发性流产的危险度较野生（T/T）基因型分别提高了0.424和0.271倍。结论：人CYP17基因启动子5＇上游-34碱基处T→C突变与中国东北地区人群复发性流产有关,C等位基因可能是复发性流产的遗传易感因素之一。
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.033 |
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".