Wastewater release and its impacts on Canadian waters
Bibliographic record
Abstract
Discharge of sewage to the environment in the form of treated or untreated wastewater can have serious impacts on human health and quality of life and on ecosystem condition. Since a previous review in 1997, upgrades to wastewater treatment facilities, along with improved source control, have produced successes in reducing loadings of certain pollutants (e.g., mercury, polychlorinated biphenyls) to Canadian waters. However, nationally, loads of phosphorus discharged from wastewater treatment facilities have not changed in recent years (2003–2008), and releases of nitrogen have increased slightly. In some locations, wastewater discharges are contributors to bacterial contamination, toxicity from heavy metals and ammonia, and eutrophication, all of which continue to threaten public and environmental health. An increasing number of studies are also demonstrating developmental, reproductive, and behavioural changes in fish and other aquatic organisms from exposure to pharmaceuticals, personal-care products, or other pollutants in domestic wastewater, even after treatment. Minimizing wastewater discharge and mitigating its effects on the environment and human health will be a challenge. It is critical that gains achieved by improved wastewater treatment and other control measures not be reversed by relaxation of efforts or by failure to keep pace with population growth.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".