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Record W2327564694 · doi:10.1061/9780784412947.304

Municipal Wastewater Effluent Strategy: Studies to Determine the Effluent Discharge Objectives for Wastewater Treatment Plants in Saskatchewan, Canada

2013· article· en· W2327564694 on OpenAlexaffabout
O. S. Thirunavukkarasu, T. Phommavong, Yee‐Chung Jin, S. A. Ferris

Bibliographic record

VenueWorld Environmental and Water Resources Congress 2013 · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsMinistry of EnvironmentWater Security AgencyUniversity of Regina
Fundersnot available
KeywordsEffluentWastewaterSewage treatmentEnvironmental scienceWaste managementEnvironmental engineeringEngineering

Abstract

fetched live from OpenAlex

Municipal wastewater usually contains many substances that may have risks for human health and environment protection. The Canadian Council of Ministers of Environment (CCME) has developed a Canada-wide Strategy for the Management of Municipal Wastewater Effluent (also called MWWE Strategy) for effluent discharged into surface water from wastewater treatment plants. The Strategy requires all municipal wastewater treatment plants in Canada including Saskatchewan that are discharging effluent into fish-bearing waters to achieve National Performance Standards (NPS) and develop site-specific Effluent Discharge Objectives (EDOs). The strategy also helps to better manage the wastewater facilities and to set up the standard for the future new facilities (CCME, 2009).

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.621

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.008
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.243
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2013
Admission routes2
Has abstractyes

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