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Record W7027176940

Building capacity for rainwater harvesting in Ontario: rainwater quality and performance of RWH systems

2008· dissertation· en· W7027176940 on OpenAlexfundaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2008
Typedissertation
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
FundersOntario Centres of Excellence
KeywordsRainwater harvestingCisternLaundryToiletWater qualityHydrology (agriculture)
DOInot available

Abstract

fetched live from OpenAlex

To promote the practice of rainwater harvesting (RWH) in Ontario, two issues surrounding urban rainwater use were examined: the performance aspects of RWH systems, and rainwater quality. This study found RWH to be a practical solution for augmenting municipal water supplies; decreasing the annual mains water use of a five person water-conserving household by 30% (65 m 3) when used for toilet flushing, laundry and outdoor use. Monitoring of RWH systems during periods of cold weather indicates that these systems can operate during winter conditions, provided that the rainwater cistern is buried below the frost penetration depth, or placed in a temperature controlled environment. A significant variation in rainwater quality was observed between sites, over time, and with treatment. The absence of heavy metals, PAHs, ' Legionella,' or 'Campylobacter' in any of the rainwater samples indicates that given post-cistern treatment, rainwater end-uses could be expanded beyond those permitted by the Ontario Building Code.

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)0.001
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 score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.224
Teacher spread0.185 · 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
Published2008
Admission routes2
Has abstractyes

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