Effects of pulp and paper mill effluent on fish: A temporal assessment of fish health across sampling cycles
Bibliographic record
Abstract
The Canadian environmental effects monitoring (EEM) program is a regulated, cyclical, industry-funded program designed to determine whether receiving water impacts exist when a mill is in compliance with its discharge limits. The results from three cycles of the fish monitoring program (1992 to 2004) are available from over 200 surveys of fish compared between sites located upstream and downstream of pulp and paper mill effluent outfalls. Previous meta-analyses have shown a national average response pattern across cycles characterized by an increase in endpoints measuring energy storage and growth and a decrease in a reproductive endpoint, consistent with a response of nutrient enrichment in combination with some form of metabolic disruption. Although the national average pattern of effects was temporally consistent, there was some variability in the magnitude of effects among cycles. Questions were raised as to whether the intercycle variability was due to changes in effluent quality or due, at least in part, to other factors. The present study compares responses over the first three cycles, and shows that the choice of sentinel species is likely to be a major contributing factor to the variability in observed effects. Subset analyses using studies from mills that used the same sentinel species across cycles reveal fairly uniform responses and little evidence of significant improvements in overall fish health from cycles one to three. However, a meta-analysis using 1991 data collected from 10 mills before the implementation of the EEM program and data from the same mills collected during cycles one to three of the program reveal significantly reduced effects on relative liver weight and potential improvements in other endpoints.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".