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Record W1845443293 · doi:10.1139/f2011-096

Wastewater release and its impacts on Canadian waters

2011· article· en· W1845443293 on OpenAlexaffvenueabout
Claire Holeton, Patricia A. Chambers, Laura Grace

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsWastewaterEnvironmental scienceSewage treatmentPollutantSewageAquatic ecosystemEutrophicationPopulationWater qualityEnvironmental engineeringEnvironmental protectionNutrientEcologyEnvironmental healthBiology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.022
GPT teacher head0.191
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations122
Published2011
Admission routes3
Has abstractyes

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