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Record W7132912274

Comparison of Pipe Loop and Pipe Section Reactor Methods for Estimating Chloramine Decay in Distribution Systems

2022· dissertation· W7132912274 on OpenAlexfundaboutno aff
Itai Arbiv

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsChloramineLoop (graph theory)Plug flowSection (typography)Pipe flowFerrousDistribution (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Despite their relative stability compared to free chlorine, chloramines are known to decay in distribution systems via surface-catalyzed reactions including ferrous oxidation and microbial nitrification. As such, the prediction of in-situ chloramine demand represents an important issue for drinking water utilities. This study compared the use of continuous-flow pipe loops and batch Pipe Section Reactors (PSRs) to assess chloramine decay using materials and flow conditions typical of distribution systems in the Greater Toronto Area, Ontario. Pipe material was observed to be the greatest determinant of chloramine decay using both PSR and pipe loop methodologies. First-order decay coefficients obtained using pipe loops were statistically similar to those for PSR trials when considering harvested lined and unlined iron piping. Overall results suggest that pipe section reactors may serve as a viable and cost-effective alternative to pipe loops for estimating the impact of operational variables on disinfectant decay in distribution systems.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.409
Teacher spread0.372 · 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 designBench or experimental
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
Published2022
Admission routes2
Has abstractyes

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