Bibliographic record
Abstract
This study was conducted to investigate the superovulation(SOV) efficiency of two different FSHs (made in Canada and China respectively ) on Poll Dorset sheep. Therefore,the experiment compared several factors on SOV,including ways of drug administration,repeated SOV,multi- or primiparous ewes, season,natural estrous and induced estrous and unknown estrous cycles. At the same time,the effects of corpora lutea degradation, follicles and estrous delayed on SOV were observed. The results of this study show that FSH (CA) had the best effect on SOV,the second was the combination of FSH (made in Ningbo and in Chinese Academy of Science). Repeated superovulation had no significant effect on SOV efficiency. Multiparous ewes had better SOV result than primiparous ewes. SOV was better in natural estrous ewes than induced estrous and unknown estrous cycle ewes. Useable embryo recovery was significantly low in ewes of corpora lutea degradation. Follicles' existing in ovary or not had no significant difference on SOV and the efficiency of SOV was significantly lower in the estrous delayed ewes than in normal estrous ewes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".