Updates and Current Challenges in Reproductive Microbiome: A Comparative Analysis between Cows and Women
Bibliographic record
Abstract
The microbiota plays an important role in numerous physiological processes, pathogenesis, development, and metabolism in different animal species. In humans, several studies have demonstrated an association between the vaginal microbiota and fertility rates, and even success in assisted reproduction techniques. In the context of cattle reproduction, although few studies have addressed the microbiota in a healthy state (which is not associated with diseases that affect the reproductive tract of cows), changes in its composition also seem to influence fertility. This review aims to explain the importance of the reproductive microbiota in female bovines and what is available in the literature regarding its possible role in increasing fertility. What are the challenges involved in this process? Future perspectives on its use and manipulation as a selection or intervention tool. Will it be possible to one day extrapolate the findings to reality and apply them in the field? In short, understanding the role of the reproductive microbiota of female bovines can signal the prospect of increasing production, whether of milk or meat, from the same number of animals, as it can optimize reproductive efficiency and perhaps become an allied tool for the economic profitability and sustainability of livestock farming.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".