Morphometric and metabolic indicators of metal stress in wild yellow perch (Perca flavescens) from Sudbury, Ontario: A review
Bibliographic record
Abstract
Eighteen lakes studied near Sudbury and across Northeastern Ontario (Canada) over a five-year period provided a wide contamination gradient of cadmium (Cd), copper (Cu) and other metals such as nickel (Ni) and zinc (Zn). All were inhabited by yellow perch (Perca flavescens), which was sometimes the only species present. Liver Cd and Cu concentrations were monitored in these lakes, in some cases for several consecutive years and for multiple seasons. This data suggests that yellow perch from clean to mildly-contaminated environments loosely control their hepatic Cu concentrations between 7 and 50 microg g dry weight(-1), and a threshold of 50 microg g dry weight(-1) is suggested as the normal range of homeostatic control. Similar data collected by others support this value. Liver Cd concentrations appeared more variable among lake samples, but consistently remained below 10 microg g dry weight(-1) in clean to mildly-contaminated lakes, also supported by data collected elsewhere. Condition factors allowed the discrimination between clean and polluted yellow perch, a conclusion consistent with data for the same species collected in the Rouyn-Noranda area (Quebec, Canada). Values of weight-to-length scaling coefficient lower than 3.0 also discriminated between clean and metal-polluted yellow perch. Finally, three studies indicated that chronic metal exposure can lead to an impairment of aerobic capacities in wild yellow perch, as indicated by lower muscle activity of citrate synthase (CS), aerobic swim performance and respiration rate. We propose that the combination of liver metal concentrations, scaling coefficient, condition factor and an indicator of physiological impairment such as muscle CS activity can provide a suitable range of parameters to adequately assess the effects of metal contamination on the health of yellow perch. Although yellow perch are ubiquitous in North America, this approach can potentially be applied to other small fish species more suitable to other study areas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".