The Aquatic Environment and Textile Mill Effluents — An Ecological Risk Assessment
Bibliographic record
Abstract
Textile mill effluents (TMEs) are wastewater discharges from textile mills that are involved in wet processes such as scouring, neutralizing, desizing, mercerizing, carbonizing, fulling, bleaching, dyeing, printing and other wet finishing activities. TMEs are complex mixtures containing a wide variety of chemicals which have a range of pH, temperature, colour and oxygen demand characteristics. Most wet processing mills in Canada discharge to municipal wastewater collection systems where those effluents receive some form of wastewater treatment. This paper reports the results of a tiered assessment approach that was used to determine the impacts on the aquatic environment of whole effluents discharged by wet processing textile mills in Canada. A conservative assessment indicated that no substantial threat to the aquatic environment was associated with TMEs receiving secondary or tertiary treatment, on- site or at a municipal wastewater treatment plant, prior to discharge to receiving waters. In the case of TMEs receiving only primary treatment or no treatment prior to discharge, a weight-of-evidence risk assessment supported the conclusion that those effluents could produce significant environmental harm in aquatic environments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".