Semen collection, characterisation and artificial insemination in the beluga (Delphinapterus leucas) using liquid-stored spermatozoa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ejaculates were collected from a beluga (Delphinapterus leucas) to gain an understanding of sperm biology and develop a short-term sperm preservation method for use in artificial insemination (AI). Ejaculate parameters and biochemistry, semen production and serum testosterone concentrations of an adult male were characterised for 21 months. Sperm viability, acrosome integrity and morphology did not change (P > 0.05) but ejaculate volume, sperm concentration and total spermatozoa per ejaculate were higher (P < 0.05) from January to June than from July to December. Peak testosterone concentrations (P < 0.05) were observed from October to April (8.0 +/- 1.6 ng mL(-1)). The effects of hyaluronic acid (HA), antioxidants, storage temperature and time on in vitro sperm characteristics were examined. Motility parameters and viability were improved (P < 0.05) when semen was stored at 5 degrees C compared with 21 degrees C. During the first 24 h of storage sperm agglutination was absent only at 5 degrees C in the presence of HA. A nulliparous 28-year-old female was inseminated endoscopically with liquid-stored semen. A pregnancy and birth of a calf was achieved following AI for the first time in this species, thereby validating both the AI technique and the fertility of beluga spermatozoa after chilled storage in a specialised diluent.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 it