Evaluation of a Wisconsin-type bioenergetics model to estimate brook charr (Salvelinus fontinalis) growth and food consumption under two salinity conditions
Bibliographic record
Abstract
In Québec, Canada, brook charr (Salvelinus fontinalis) is the most sought-after species for recreational fisheries, which makes it economically important. To improve population monitoring and better anticipate climate change impacts on brook charr, bioenergetics models can be useful. The objective of this research was to evaluate the performance of a resident brook charr Wisconsin Energy Budget (WEB) model applied to an anadromous strain under two salinity treatments. Growth and food consumption were predicted by the model and compared to the observed values obtained after a 60 day experiment in the laboratory on fish reared in fresh or brackish water. Predictions for fish reared in fresh water better estimated growth rate and consumption than for fish reared in brackish water, for which growth was overestimated and consumption was underestimated. Overall, these results suggest that there is a difference for the WEB model’s predictions depending on the salinity and that observed food consumption is predicted more accurately than growth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".