Opinion & HypothesisCould early aspirin prophylaxis prevent against preterm birth?
Bibliographic record
Abstract
A growing body of evidence suggests that defective placentation may play a major role in the genesis of preterm birth, indicating that preeclampsia, intra-uterine growth restriction (IUGR), and spontaneous preterm birth can share a similar mechanism of disease. A recent meta-analysis of low-dose aspirin trials for the prevention of preeclampsia and IUGR in high-risk women demonstrated that, when started early in gestation, aspirin could prevent more than half of preeclampsia and IUGR cases but was also linked with a significant decrease of preterm births (relative risk 0.22, 95% confidence interval: 0.10-0.49). Unfortunately, most studies did not report specific data on the cause of preterm deliveries and, therefore, we could not estimate the proportion of this effect that could be related to spontaneous preterm births. Therefore, we hypothesize that low-dose aspirin could become an additional weapon in the prevention of preterm births and we suggest that further studies should be performed in this area of research.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.010 |
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".