Influence of food web structure on the growth and bioenergetics of lake trout (<i>Salvelinus namaycush</i>)
Bibliographic record
Abstract
In this study, we compared energy budgets of lake trout (Salvelinus namaycush) populations in contrasting food webs. Nonpiscivorous lake trout (NPLT) reached a much smaller size and grew at a much slower rate than piscivorous lake trout (PLT) populations. Food consumption rates were, on average, 23 times higher in NPLT when they were expressed on a wet weight basis. However, only a slight (less than 10%) difference in their energy intake was detected once consumption rates were corrected for differences in prey caloric content. Growth efficiency was approximately two times lower in NPLT compared with PLT, while their metabolic costs were higher and their assimilation efficiency was lower. It is most likely that the increased metabolic costs were associated with higher foraging costs, since more feeding attempts must be made to acquire a given quantity of food when fish are feeding on smaller prey. Furthermore, the portion of indigestible matter is likely to be higher in the diet of NPLT than in PLT (i.e., chitin vs. bone). These results are consistent with theoretical models of fish growth that show that lake trout must have access to larger prey, even if they are rare, to reach larger body sizes.
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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 | 0.000 | 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".