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Record W2197857799

Metro Vancouver Region's Combined Sewer and Sanitary Sewer Overflows Monitoring and Risk Assessment

2014· article· en· W2197857799 on OpenAlexaboutno aff
Andjela Knežević-Stevanović, Lynn Landry, Farida Bishay, J. E. Mazur, Glen Esquera

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsCombined sewerSanitary sewerSewerageEnvironmental scienceWater resource managementStormwaterEnvironmental engineering
DOInot available

Abstract

fetched live from OpenAlex

Metro Vancouver's Integrated Liquid Waste and Resource Management Plan (ILWRMP) states that no new combined sewers will be constructed, and that existing combined sewers will be separated into storm and sanitary sewers via infrastructure replacement or sewer capacity upgrading programs. The ILWRMP also requires prevention of wet weather SSOs for 24 hour storm events of less than 1 in 5 years, outlines a commitment to characterize the quality of CSO and SSO discharges and assess their impact on the receiving water bodies. Samples for both CSO and SSO monitoring programs are collected using automated samplers, triggered by a supervisory control and data acquisition system (SCADA), based on wastewater system levels. For CSOs and SSOs sample collection is done during or just prior (respectively) to the initial discharge with the intent of capturing the first flush when levels and loadings of contaminants are highest and represent worst case scenarios. CSO and SSO quality are characterized through analyses of samples for bacteriology, physico-chemical constituents and toxicity. Parameters are selected based on their potential presence in wastewater at levels of concern, usefulness as indicators of ecological or human health impacts, or are required for consideration of potential mitigation actions. The monitoring information is further used in human health and ecological risk assessment. The findings of the risk assessment are used for negotiation with the regulators and prioritization and design of mitigation infrastructure when required.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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