Long-term polychlorinated biphenyl elimination by three size classes of yellow perch (<i>Perca flavescens</i>)
Bibliographic record
Abstract
Three size classes of yellow perch (Perca flavescens) were dosed with a polychlorinated biphenyl (PCB) mixture and allowed to depurate the chemicals over 1 year while reared in 5000 L experimental tanks maintained under ambient environmental conditions. During the summer, PCB elimination rate constants for small perch (mean = 10.1 g) averaged approximately three times those calculated for medium-sized individuals (mean = 45.9 g) and four times those determined for the largest fish (mean = 86.7 g). Significant differences in PCB congener depuration were observed among the three size classes with negligible elimination of congeners of the octanol-water partition coefficient (log Kow) > 6.5 occurring for the two larger size classes. Over the winter months, medium and large perch eliminated PCB 19 only, the least hydrophobic congener, with no elimination of PCBs of log Kow > 5.8 observed for the smallest individuals. An increase in lipid-normalized PCB concentrations was observed during the overwinter period because of the depletion of lipids as an energetic reserve. For medium and large perch, this increase was sufficient to overwhelm any elimination achieved during the spring and summer seasons. These results demonstrate that the allometry of species bioenergetics and seasonal temperature fluctuations are responsible for the degree of chemical biomagnification observed in aquatic food webs.
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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 | 0.000 | 0.000 |
| 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".