<i>In vitro</i> fertilization experiments using sockeye salmon reveal that bigger eggs are more fertilizable under sperm limitation
Bibliographic record
Abstract
Although theory and widespread evidence show that the evolution of egg size is driven primarily by offspring and maternal fitness demands, an additional explanation invokes sperm limitation as a selective force that could also influence egg size optima. Levitan proposed that constraints from gamete encounter in external fertilization environments could select for enlargement of ova to increase the physical size of the fertilization target. We test this theory using in vitro fertilization experiments in an externally fertilizing fish. Sockeye salmon (Onchorhyncus nerka) females show considerable between-individual variation in ovum size, and we explored the consequences of this natural variation for the fertilization success of individual eggs under conditions of sperm limitation. By engineering consistent conditions where in vitro fertilization rate was always intermediate, we were able to compare the sizes of fertilized and unfertilized eggs across 20 fertilization replicates. After controlling for any changes in volume through incubation, results showed that successfully fertilized eggs were significantly larger than the eggs that failed to achieve fertilization. Under conditions without sperm limitation, fertility was unaffected by egg size. Our findings therefore support Levitan's theory, demonstrating empirically that some element of egg size variation could be selected by fertilization demands under sperm limitation. However, further research on sperm limitation in natural spawnings is required to assess the selective importance of these results.
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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 | 0.001 |
| 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".