Seasonal and regional variations in metal contamination and condition indicators in yellow perch (Perca flavescens) along two polymetallic gradients. II. Growth patterns, longevity, and condition
Bibliographic record
Abstract
Wild yellow perch (Perca flavescens) were sampled from five lakes in each of two metal contamination gradients in Sudbury, Ontario, Canada (n = 1324) and Rouyn- Noranda, Qu´ebec, Canada (n = 1125) in the spring and summer of 2002 and 2003, respectively, in order to examine growth patterns, longevity, and the influences of season and region on fish condition. Fish from Rouyn-Noranda began rapid growth at a young age, whereas fish from Sudbury lakes showed slow growth rates between ages 0–3, after which growth rates improved. Fish from contaminated lakes grew faster and died younger than fish from reference lakes in both contamination gradients. Fish from Sudbury had lower condition than in Rouyn-Noranda, higher condition occurred in summer than spring, and fish from contaminated lakes had lower condition than those from cleaner lakes. Tissue Zn concentrations were correlated with fish condition and showed strong temporal stability. However, it is more likely that Zn covariates, such as Cd or Cu (which were more temporally variable) influenced condition, suggesting that long-term, broad-scale processes are more important than short-term, lake-specific processes for establishing growth patterns, longevity, and fish condition in metal-contaminated systems. Results from this study reveal that fish condition must be interpreted in the light of regional, seasonal, and other factors that can potentially influence fish growth patterns. Ecological risk assessments that fail to take these factors into account may draw erroneous conclusions about risk to indigenous populations.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".