Bibliographic record
Abstract
自1974年,明尼苏达大学Sutherland等实施了世界上首例人胰岛细胞移植治疗1型糖尿病以来[1],到今天已经有将近40年的临床历史了.然而胰岛细胞移植术后的临床疗效仍然欠佳.有报道显示[2],尽管临床上已经改良实施了Edmonton方案,在胰岛细胞移植术1 000 d后也仅有12％的受者仍能维持胰岛素非依赖状态.目前认为,影响临床胰岛细胞移植术后疗效的因素主要包括免疫排斥因素和非免疫排斥因素导致的胰岛损伤、丢失.本文将主要针对胰岛细胞移植术后非免疫排斥因素对其术后疗效的影响,以及胰岛细胞移植术后功能性胰岛细胞的监测方法综述如下。
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".