Adaptability and potential for treatment of placental functions to improve embryonic development and postnatal health
Bibliographic record
Abstract
For an organ that is so critical for life in eutherian mammals, the placenta hardly gets the attention that it deserves. The placenta does a series of remarkable things, including implanting the embryo in the uterus, negotiating with the mother for nutrients but also protecting her health during pregnancy, helping establish normal metabolic and cardiovascular function for life postnatally (developmental programming) and initiating changes that prepare the mother to care for and suckle her young after birth. Different lines of evidence in experimental animals suggest that the development and function of the placenta are adaptable. This means that some of the changes observed in pathological pregnancies may represent attempts to mitigate the impact of fetal growth and development. Key and emerging concepts are reviewed here concerning how we may view the placenta diagnostically and therapeutically in pregnancy complications, focusing on information from experimental studies in mice, sheep and cattle, as well as association studies from humans. Hundreds of different genes have been shown to underlie normal placental development and function, some of which have promise as tractable targets for intervention in pregnancies at risk for poor fetal growth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".