Male involvement in fertility and factors affecting semen quality in bulls
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
Fertility varies substantially among bulls. In general, methods to predict fertility are better for identifying bulls with low fertility than for ranking bulls with good to excellent fertility. Compensable sperm abnormalities can be overcome by increasing the dose used for artificial insemination; these are attributed to sperm reaching and penetrating the zona pellucida. In contrast, increasing the insemination dose does not improve fertility for uncompensable defects, implying that the sperm are able to cause fertilization and initiate development, but they do not sustain embryogenesis. Bull testes must be 2 to 6°C cooler than core body temperature for fertile sperm; consequently, increased testicular temperature reduces semen quality. Increased nutrition before 30 weeks of age increased luteinizing hormone pulse frequency, hastened puberty, and increased testicular size at maturity in bulls. However, attempts to correct nutritional deficiencies present during calfhood by supplemental nutrition later in life were unsuccessful.
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 | 0.000 | 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) | 0.000 | 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