Effects of feeding ration on larval swimming speed and responsiveness to predator attacks: implications for cohort survival
Bibliographic record
Abstract
We conducted laboratory experiments to examine the effects of feeding ration on the routine swimming speed of larval striped bass (Morone saxatilis) and their responsiveness to simulated-predator attacks. Striped bass were reared in low (7 prey·L-1), medium (354 prey·L-1), or high (740 prey·L-1) prey treatments from age 4 to 14 days posthatch. Larvae reared in the low-prey treatment had slower routine swimming speeds and shorter reactive distances and were less responsive to simulated-predator attacks. These differences were most pronounced after age 10 and appeared to be an effect of deteriorating larval condition rather than an effect of size. Simulation models were constructed for two potential fish predators, Alosa aestivalis and Pomoxis nigromaculatus, to examine how variation in growth rate, swimming speed, and responsiveness to predator attacks might influence mortality rate. Our simulations predicted that cohort mortality rate would decrease with increasing larval growth rates, even though faster routine swimming speed and growth rate increased encounter rates with predators. The influence of larval growth rate and responsiveness on mortality rate varied between the two predators, but cohorts experiencing no growth always had the greatest mortality rate.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 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".