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Record W2944892644 · doi:10.1680/jenhh.18.00025

Waterworks in a changing climate: the R.C. Harris filtration plant, Toronto, Canada

2019· article· en· W2944892644 on OpenAlexaffabout
Susan M. Ross

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Engineering History and Heritage · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsCarleton University
Fundersnot available
KeywordsClimate changeWater supplySustainabilityWatershedEnvironmental planningWater resourcesCultural heritageEnvironmental scienceEnvironmental resource managementWater resource managementCivil engineeringEnvironmental engineeringGeographyEngineeringArchaeologyComputer scienceGeology

Abstract

fetched live from OpenAlex

This research paper reviews the literature in an area of engineering heritage requiring further examination, the impact of climate change on historic urban water supply systems. Many opportunities exist to enhance the sustainability of historic waterworks still in operation in order to help mediate climate change effects. This must include mitigating climate change impacts on sources of potable water, such as by implementing strategies for water-efficient landscape design, while considering possible uses of the visible elements of the system, such as water treatment plants, to draw attention to this engineering heritage’s continued and critical role. The R.C. Harris filtration plant is the main water treatment plant for the Greater Toronto Area in Canada, drawing water from Lake Ontario. This iconic ‘Palace of Purification’ has been in continuous use since 1941 and was declared a National Historic Civil Engineering Site in 1992. In 2013, it was still producing nearly 40% of Toronto’s tap water. Examination of this plant serves to illustrate the interconnection of a system’s historic design and its water source’s watershed as heritage, to discuss expected impacts of climate change and explain not only some of the possibilities for mitigation, but also eventual necessary and challenging adaptations to changing treatment needs.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0120.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.004
GPT teacher head0.139
Teacher spread0.135 · 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 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
Published2019
Admission routes2
Has abstractyes

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Same venueProceedings of the Institution of Civil Engineers - Engineering History and HeritageSame topicUrban Stormwater Management SolutionsFrench-language works237,207