Changes in the condition, early growth, and trophic position of lake trout (<i>Salvelinus namaycush</i>) in response to an experimental aquaculture operation
Bibliographic record
Abstract
We analyzed changes in the condition, early growth, and resource use of lake trout (Salvelinus namaycush) from a Boreal Shield lake in response to an experimental aquaculture operation. Annual small-scale commercial production of rainbow trout (Oncorhynchus mykiss) resulted in increased lake trout body condition during aquaculture operations, which was positively related to minnow catch per unit effort (CPUE). Incremental increases in growth led to larger lake trout following aquaculture. While the littoral energy assimilated by lake trout did not change linearly from 2002 to 2009, we observed a shift towards littoral energy use in the last year of aquaculture and for 2 years after the experiment, coincident with low densities of Mysis diluviana. Lake trout trophic position declined from 2002 to 2009, suggesting increased foraging on secondary versus tertiary consumers. Minnow and slimy sculpin (Cottus cognatus) CPUE increased by 5.2- and 5.5-fold, respectively, and Mysis diluviana densities decreased by 93%. Changes observed in the experimental lake were much greater than those observed in a nearby reference lake. Our results suggest that moderate nutrient enrichment from aquaculture may benefit lake trout in oligotrophic Boreal Shield lakes.
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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 | 0.001 | 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".