Organochlorine Compounds in Trout from Lakes over a 1600 Meter Elevation Gradient in the Canadian Rocky Mountains
Bibliographic record
Abstract
The effect of altitude on the concentration and composition of organochlorine compounds (OC) in troutwas investigated along an elevation gradient of 1600 m in the Canadian Rocky Mountains. The eight lakes sampled were within or adjacent to national parks in sparsely settled parts of Alberta and British Columbia, thus contaminants were assumed to have derived from long-range atmospheric transport. Concentrations of several OCs in trout increased significantly with lake elevation. In general, these increases were most pronounced for the higher K(ow) pesticides (i.e., dieldrin and DDTs), and less pronounced for lower K(ow) pesticides (e.g., HCHs and HCB) and PCBs. Most OC concentrations in trout were inversely correlated with fish growth rate. Growth rate explained more of the variation for some OCs (particularly PCBs) than lake elevation. Differences in trophic position (indicated by delta15N) explained little of the variation in OC concentration in comparison to other factors such as lake elevation and the growth rate and age of trout. Using principal component analysis (PCA), we identified the importance of lake elevation and octanol/water partition coefficient (K(ow)) to the OC composition of trout.
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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 | 0.000 |
| Scholarly communication | 0.001 | 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".