No effect of sperm interactions or egg homogenate on sperm velocity in the blue mussel,<i>Mytilus edulis</i>(Bivalvia: Mytilidae)
Bibliographic record
Abstract
We investigated the possible effects of sperm interactions and homogenized eggs on sperm velocity in blue mussels ( Mytilus edulis L., 1758) using computer-assisted sperm analysis. To test whether sperm competition results in an increase in sperm velocity, using seven pairs of males, we compared the mean curvilinear and average path velocities of sperm from two males measured separately with the corresponding values from a mixture of sperm from the same two males. To test whether the presence of eggs results in an increase in sperm velocity, we compared curvilinear and average path velocities from 11 individual males with the corresponding measures from the same 11 sperm samples mixed with aliquots of homogenized eggs. Neither experimental treatment resulted in an increase in sperm velocity. We interpret these results as consistent with the hypothesis that mussel sperm have been selected to immediately begin swimming at an optimal initial velocity that is adaptive for the particular environment in which they are located. Critical factors affecting the evolution of sperm velocity for broadcast spawning, external fertilizers such as M. edulis likely include population density and intraspecific spawning synchronicity. As has been suggested by others, the importance of sperm limitation (i.e., having much less than 100% of eggs being fertilized in the wild) may be as important an evolutionary driving force in broadcast spawning invertebrates as sperm competition is in internally or directly fertilized species.
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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 | 0.001 |
| 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) | 0.002 | 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".