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Record W3119222905 · doi:10.2166/wqrj.2020.025

Role of wastewater treatment in COVID-19 control

2021· article· en· W3119222905 on OpenAlexaff
Chao Chen, Keith Hayward, Stuart J. Khan, Banu Örmeci, Sudhir Pillay, Joan B. Rose, Joseph V. Thanikal, Tong Zhang

Bibliographic record

VenueWater Quality Research Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsCarleton University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicTask (project management)Control (management)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Task force2019-20 coronavirus outbreakRelation (database)BusinessEngineering ethicsRisk analysis (engineering)Knowledge managementEnvironmental planningEngineeringComputer sciencePolitical scienceMedicineEnvironmental scienceSystems engineeringVirologyArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The International Water Association (IWA) initiated a Task Force in April 2020 to serve as a leadership team within IWA whose role is to keep abreast and communicate the emerging science, technology, and applications for understanding the impact and the ability to respond to the COVID-19 pandemic and specifically designed for water professionals and industries. Expertise was nominated across the world with the purpose of collectively providing the water sector with knowledge products for the guidance on the control of COVID-19 and other viruses. This review paper developed by a working group of the IWA Task Force focuses on the control of COVID-19. The purpose of this review paper is to provide an understanding of existing knowledge with regards to COVID-19 and provide the necessary guidance of risk mitigation based on currently available knowledge of viruses in wastewater. This review paper considered various scenarios for both the developed world and the developing world and provided recommendations for managing risk. The review paper serves to pool the knowledge with regards to the pandemic and in relation to other viruses. The IWA Task Team envisage that this review paper provides the necessary guidance to the global response to the ongoing pandemic.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.031
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.222
GPT teacher head0.475
Teacher spread0.253 · 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 teacher head, 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

Citations22
Published2021
Admission routes1
Has abstractyes

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