Nuclear magnetic resonance spectroscopy of bovine ovarian follicular fluid at four selected times of the oestrous cycle
Bibliographic record
Abstract
The objective of the study was to determine if nuclear magnetic resonance (NMR) spectral features of ovarian follicular fluid were correlated with the physiological status of follicles so that we could assess the feasibility of using NMR spectroscopy during assisted reproduction therapy. Thirty-five sexually mature, nullparious heifers were monitored by transrectal ultrasonography to assess their follicle wave status during the oestrous cycle. Ovariectomies were performed on Day 3 of wave 1 (D3W1, n = 10), Day 6 of wave 1 (D6W1, n = 9), Day 1 of wave 2 (D1W2, n = 9), or in the immediate preovulatory period of at least 17 days after ovulation (De17, n = 9). Follicle status was determined to be dominant or subordinate. Follicular fluid was extracted from the follicles and NMR spectra were collected. Principal components were extracted from ratios of line amplitudes and tested for effects of follicle status (dominant v. subordinate) and cycle time point (D1W3, D1W6, D1W2 and De17) using multivariate analysis of variance. For most line ratio combinations, main effects of status, time point and their interaction were found (P < 0.05). We concluded that NMR spectra may be used for the determination of ovarian follicle physiological status.
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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 | 0.000 |
| 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) | 0.000 | 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 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".