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Record W3009958443 · doi:10.1115/nawtec9-106

A Canadian Perspective on Waste-to-Energy

2001· article· en· W3009958443 on OpenAlexaffabout
Rob C. Rivers, Nenad Knezev

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsInro Consultants (Canada)
Fundersnot available
KeywordsIncinerationWaste managementScrubberPollution preventionPollutionUpgradeChristian ministryAir pollutionEnvironmental scienceGeneral partnershipEngineeringEnvironmental engineeringBusinessFinanceComputer science

Abstract

fetched live from OpenAlex

Abstract Public private partnership has played a mayor role in development and successful operation of the current KMS Peel Waste-to-Energy Plant located in Peel Region, Ontario. On December 10, 1998 KMS Peel Inc. and the Region of Peel entered into an agreement to expand the waste-to-energy facility by 36,000 tonnes (one additional incineration unit). Due to expansion, new, more stringent emission limits were imposed by the latest Ontario Ministry of Environment A-7 Guideline and the Canada-Wide Standards developed by Canadian Council of Ministers of Environment. A Selective Catalytic Reduction (SCR) system with a sodium tetrasulphide injection was selected to supplement the existing dry scrubber/fabric filter air pollution control system for additional reduction in mercury, nitrogen oxides and dioxins/furans emissions. With the upgraded air pollution control technology, the facility will be able to meet the latest emission standards and, to a certain degree, any new standards that may be enforced in future years. This paper outlines a partnership model that has been successfully implemented in Ontario and has contributed to the public accepting waste-to-energy as integral part of the waste management system, ultimately resulting in facility expansion. It also describes the current facility and upgrade to the existing air pollution control system.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score0.996

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.004

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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2001
Admission routes2
Has abstractyes

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