Do the blood anti‐Müllerian hormone concentrations in young females correlate with the ovarian follicular population later in life in water buffalo?
Bibliographic record
Abstract
In this longitudinal study, the anti-Müllerian hormone (AMH) levels in blood were determined in 32 Murrah buffalo females at 8, 10, 12, 16 and 19 months of age when females were synchronized and the antral follicular population (AFP) was estimated. Correlations of AFP to the AMH level at 19 months of age and retrospectively to younger ages were investigated. Then females were split into high and low AFP, and their AMH levels were compared for all ages and tested as predictors of AFP categories. The highest AMH level (p < .05) was detected at 8 months, reducing but not differing (p > .05) at 10, 12 and 16 months then reducing again (p < .05) at 19 months of age. The mean AFP was 17.6 ± 6.3 follicles, and it was positively correlated with AMH in all ages tested. High AFP females had approximately two times more antral follicles than low AFP (p < .05) and their AMH levels were higher (p < .01) than in low AFP ones in all ages. Only at 8 months, AMH levels can be used to precociously detect high AFP heifers (a cut-off point of 464.7 pg/mL; p < .05), while low AFP heifers could be detected by AMH measurements at 8, 10, 12 and 16 months of age (p < .05). We conclude that AMH of buffalo calves correlates with AFP of heifers later in life and depending on the age, its levels could be used to identify future females with low or high AFP.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".