Complying with Effluent Toxicity Regulation in Canada
Bibliographic record
Abstract
Abstract A questionnaire was sent to 75 mills in Canada requesting information on compliance in 1999 with respect to the toxicity regulation for liquid discharges. This regulation requires that at least 50% of rainbow trout and Daphnia magna survive in the discharge from the mill in toxicity tests. Of the 74 mills that responded, 81% and 74% reported no toxicity failures for process effluents in rainbow trout and Daphnia magna tests, respectively. For mills with infrequent or no toxicity episodes during the year (1 or 0 for trout; 1–4 or 0 for Daphnia magna), 89% and 92% of the mills met this criterion for trout and Daphnia magna tests, respectively. In addition to process effluents, 28 mills had separate cooling water discharges and, of these, ten experienced at least one episode of cooling water toxicity. Ammonia and accidental spills were most frequently cited by the mills as likely causes of process effluent toxicity. The most frequent causes cited for cooling water toxicity were chlorine and accidental contamination from other sources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 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 teacher head, 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".