Impacts of altered benthic invertebrate communities on the feeding ecology of yellow perch (<i>Perca flavescens</i>) in metal-contaminated lakes
Bibliographic record
Abstract
Metal contamination can disrupt trophic links in food webs by altering the taxonomic composition and size structure of benthic macroinvertebrate communities. Benthic macroinvertebrates and yellow perch (Perca flavescens) were collected from six lakes along a gradient of cadmium (Cd) and copper (Cu) contamination in Quebec, Canada. The two most contaminated lakes had significantly lower densities of several benthic macroinvertebrate taxa and significantly lower Shannon's index than less contaminated lakes. The stomach contents of perch from the most contaminated lakes were less diverse, with a greater reliance on chironomids and (or) zooplankton than perch from other study lakes. The size of prey in perch from the most contaminated lakes did not increase with age and the mean prey size was smaller than in other, less contaminated lakes. Perch from lakes with medium to low levels of contamination weighed significantly more than perch from lakes with high levels of contamination. This reduction in growth is attributed to the increased costs of foraging on a simplified prey base in metal-contaminated systems.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".