Évolution de la progestéronémie au cours de la gestation chez la chienne : étude rétrospective à partir des données du CERCA de 2019 à 2022
Bibliographic record
Abstract
Progesterone is a hormone secreted by the ovarian corpus luteum, essential for maintaining pregnancy in the bitch, which does not produce progesterone by placental relay. This hormone is involved in the development of the endometrium and inhibits uterine contractions, so any abnormal drop in progesterone levels in a pregnant bitch could lead to cessation of gestation, known as luteal insufficiency. Our retrospective study included 349 bitches and 964 progesterone blood samples from non-pregnant bitches and pregnant bitches, supplemented or not, which enabled us to describe, for pregnant bitches, a decreasing progesteronemia kinetics with a plateau between days 31 and 40 post ovulation. We have also shown that large bitches weighing between 20 and 40 kg have physiologically lower progesteronemia than small bitches weighing less than 10 kg at the same stage of gestation, which is also the case for certain breeds (German Shepherd, White Swiss Shepherd and Newfoundland), without however demonstrating that this lower progesteronemia requires progesterone supplementation to bring gestation to term. Indeed, it seems that bitches at CERCA are supplemented at a fairly early stage and that this significantly increases progesterone levels, which are close to those of unsupplemented bitches. However, we did not demonstrate the need for supplementation to bring these pregnancies to term, and further studies are therefore required to assess the impact of supplementation or non-supplementation on the course of gestation in the above-mentioned breeds, as well as any associated side effects.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".