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Record W1966151277 · doi:10.1080/10643380601174764

Particle-Associated Viruses in Water: Impacts on Disinfection Processes

2008· article· en· W1966151277 on OpenAlexaff
Michael R. Templeton, Robert C. Andrews, Ron Hofmann

Bibliographic record

VenueCritical Reviews in Environmental Science and Technology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsParticle (ecology)Environmental scienceWastewaterWater disinfectionMicroplasticsCurrent (fluid)Environmental engineeringWaste managementBiochemical engineeringEnvironmental chemistryEcologyBiologyChemistryEngineering

Abstract

fetched live from OpenAlex

Studies have shown that viruses are frequently attached onto or enmeshed within suspended particles in natural water and wastewater and that this viral–particle association can impede disinfection processes in some circumstances. This article summarizes the current state of knowledge of the occurrence of particle-associated viruses in the aquatic environment and the reported subsequent impacts on disinfection processes. The intention is that this article will help guide future research and aid regulators attempting to address the disinfection of particle-laden waters.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.034
GPT teacher head0.305
Teacher spread0.271 · 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
GenreReview

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

Citations115
Published2008
Admission routes1
Has abstractyes

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