Development of biological nutrient removal technology in western Canada
Bibliographic record
Abstract
Biological nutrient removal (BNR) technology for wastewater treatment was originally imported from South Africa in the early 1980s to protect the water quality of Okanagan Lake in central British Columbia from the effects of eutrophication. Since that time, more than 10 BNR plants have been built in western Canada, with capacities ranging from 2000 to 500 000 m 3 /d. As a result of the interaction among university researchers, plant designers, and plant operators, considerable progress has been made in refining the understanding of process and adapting the technology for cold climates. Consulting engineers from western Canada are now successfully competing in the international marketplace in the application of BNR technology in the U.S.A., the U.K., Europe, Asia, and Australia. Key words: wastewater treatment, western Canada, biological nutrient removal, nitrogen removal, phosphorus removal, cold climate, technology development.
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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 | 0.000 | 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) | 0.000 | 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 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".