Twin pregnancy experimental model for transvaginal ultrasound-guided twin reduction in mares.
Bibliographic record
Abstract
Multiple pregnancies are still an important cause of noninfectious abortion, stillbirth, neonatal mortality, and significant delays in reproductive performance in mares. Despite new management techniques, reduction in multiple pregnancies is an ongoing preoccupation and challenge for the equine veterinarian. The aim of the present study was to establish a twin pregnancy experimental model in the mare to study the effectiveness of a transvaginal ultrasound-guided embryonic vesicle injection. Mares in heat were inseminated and then received an embryo at day 7 of the estrous cycle. At days 14 and 30, 53.5% (n = 23) and 23% (n = 10) of the mares, respectively, were carrying twins. Twin pregnancies were reduced at day 30 by transvaginal ultrasound-guided puncture of the embryonic vesicle (control, n = 5) or by transvaginal ultrasound-guided injection (TVUEVI) of 25 mg of amikacin into the embryonic vesicle (n = 5). The TVUEVI treatment had a 40% success rate and no significant variations in progesterone and prostaglandin metabolite were observed. Even though the technique does not seem very effective, the experimental model could be useful for clinical research in embryo reduction and early embryonic loss.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".