FERTILIZATION SELECTION ON EGG AND JELLY-COAT SIZE IN THE SAND DOLLAR DENDRASTER EXCENTRICUS
Bibliographic record
Abstract
Organisms with external fertilization are often sperm limited, and in echinoids, larger eggs have a higher probability of fertilization than smaller eggs. This difference is thought to be a result of the more frequent sperm-egg collisions experienced by larger targets. Here we report how two components of egg target size, the egg cell and jelly coat, contributed to fertilization success in a selection experiment. We used a cross-sectional analysis of correlated characters to estimate the selection gradients on egg and jelly-coat size in five replicate male pairs of the sand dollar Dendraster excentricus. Results indicated that eggs with larger cells and jelly coats were preferentially fertilized under sperm limitation in the laboratory. The selection gradients were an average of 922% steeper for egg than for jelly-coat size. The standardized selection gradients for egg and jelly-coat size were similar. Our results suggest that fertilization selection can act on both egg-cell and jelly-coat size but that an increase in egg-cell volume is much more likely to increase fertilization success than an equal change in jelly-coat volume. The strengths of the selection gradients were inversely related to the correlation of egg traits across replicate egg clutches. This result suggests the importance of replication in studies of selection of correlated characters.
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.
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 | 0.001 | 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".