Bibliographic record
Abstract
目的：对定量比值法检测葡萄糖-6-磷酸脱氢酶（G6PD）活性的方法进行实验评价。方法：用日立7600型生化分析仪对改良G6PD定量比值法试剂盒进行精密度、线性、干扰和稳定性实验，对该方法作出评价。结果：G6PD酶活性在800-10000U／L、6PGD酶活性在1100—5000U／L之间批内CV小于10％；G6PD酶在0—10000U／L和6PGD酶在0～5000U／L活性之间线性良好；干扰实验显示对胆红素、血红蛋白、甘油三酯均具有较强的抗干扰能力：稳定性实验显示标本2．8℃存放10d结果稳定。结论：该方法、精密度良好、线性、抗干扰能力和稳定性能都较好，能够满足临床常规检验的需要，适合常规推广使用。
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".