Plasma progesterone profiles in Beagle bitches with and without the whelping experience
Bibliographic record
Abstract
The aim of this study was to investigate differences between the progesterone profiles of Beagle bitches with (multiparous) and without (nulliparous) the whelping experience and to examine whether the selection of bitches by progesterone analyses before the programmed mating improved the whelping rates. In the first experiment, the progesterone profiles of nulliparous and multiparous bitches were evaluated from Days 1 to 13 (onset of prooestrus = Day 0). The mean duration of the elevation in progesterone levels (> 2 ng/mL) after the onset of prooestrus tended to be approximately 1 day shorter in nulliparous bitches (7.7 days) than in multiparous bitches (8.5 days). In the second experiment, progesterone analyses in the bitches were carried out once on Days 4, 5 or 6. Bitches with progesterone levels of > 10 ng/mL were excluded from mating because it was unclear when the progesterone levels reached > 10 ng/mL considering the optimal date for mating. No significant differences were observed in the percentages of bitches excluded from mating and in the whelping rates of the mated bitches between the groups, irrespective of the day of progesterone analysis and the type of bitch. In conclusion, the initial elevation of progesterone levels was of shorter duration in nulliparous bitches. The selection of bitches by the measurement of progesterone levels once before mating was not effective for the programmed mating.
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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) | 0.002 | 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".