Energetic cost of reduced foraging under predation threat in newly hatched ocean pout
Bibliographic record
Abstract
Previous research has shown that young fishes will decrease foraging activity while in the presence of a predatory threat.In most of these studies, however, individuals have been exposed to acute pulses of predatory threat of short duration; thus, little is known about the long-term impacts of predatory threat on development in newly hatched fish.In the present study, newly hatched ocean pout Macrozoarces americanus were visually exposed to predatory juvenile Atlantic cod Gadus morhua for 6 h per day during the feeding period.At 3°C, 8 wk old pout not exposed to predators were significantly larger (standard length and wet mass), and had a higher hepatosomatic index than fish exposed to predators.Pout exposed to predators also had lower levels of whole-body phospholipids and triacylglycerol, as well as decreased levels of essential fatty acids (arachidonic acid and eicosapentaenoic acid).Interestingly, there were no differences in size, hepatosomatic index or lipid content between the 2 treatments when the experiment was performed at 8°C, despite a decrease in foraging activity of the pout exposed to predators at this temperature.These results suggest that frequent predatory threat can affect the development of newly hatched fishes, and that temperature can affect the ability to observe growth trade-offs when performing threat-sensitive foraging experiments with ectotherms.
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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 | 0.000 | 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 | 0.001 |
| 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".