Influence of lake chemistry and fish age on cadmium, copper, and zinc concentrations in various organs of indigenous yellow perch (<i>Perca flavescens</i>)
Bibliographic record
Abstract
Concentrations of Cd, Cu, and Zn were determined in various organs of juvenile yellow perch (Perca flavescens) collected from eight lakes located along a metal concentration gradient. Metal exposure was evaluated on the basis of the free ambient Cd2+, Cu2+, Zn2+, and Ca2+ concentrations, as estimated from chemical equilibrium simulations using the ambient water chemistry data. Based on regression analyses, lake water Ca2+ and H+ did not significantly influence the steady-state metal concentrations in various body parts of yellow perch. Cadmium concentrations were significantly higher in the gastrointestinal tract than in the gills, suggesting that uptake of this metal from food is more important than uptake from water. Variations in the contribution of each organ to the total Cd and Cu burdens revealed a possible dysfunction in liver excreting capacities in the fish from the most highly contaminated lakes. Additionally, measurements on yellow perch from 0 to 10 years old (N = 81) collected from a single lake suggest that Cd concentrations in some organs increase with fish age, which we interpret to be linked to changes in fish growth rate with age.
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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".