Do the fastest sperm within an ejaculate swim faster in subordinate than in dominant males of Arctic char?
Bibliographic record
Abstract
Theoretical models predict that subordinate males should have higher sperm velocity to compensate for their disadvantaged mating role and because they experience sperm competition more frequently than dominant males. Differences in mean velocity between sperm of dominants and subordinates in the predicted direction are also documented for a few species, including the Arctic char, Salvelinus alpinus (L., 1758). Yet, this difference in mean velocity does not imply that the fastest sperm within an ejaculate, which are those most likely to fertilize eggs, swim faster in subordinates than in dominants. We studied the 5% and 10% fastest sperm cells in ejaculates of dominant and subordinate Arctic char. Before individuals attained their status, there were no differences in velocity between the fastest sperm of males that later became dominant or subordinate. Yet, after establishment of social position, subordinates showed significantly higher sperm swimming speed of the fastest cells in the first 30 s post activation (i.e., at 15, 20, and 30 s post activation). Males that became subordinates showed no change in sperm speed of the fast cells compared with those at pre-trial levels, whereas males that became dominant reduced the speed of their sperm (15 s post activation) compared with those at pre-trial levels. Our results suggest that males which attain social dominance are unable to maintain high sperm velocity, even among the small fraction of the fastest cells.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".