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Record W3036521204 · doi:10.1002/aws2.1186

Considerations for large building water quality after extended stagnation

2020· review· en· W3036521204 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAWWA Water Science · 2020
Typereview
Languageen
FieldArts and Humanities
TopicConservation Techniques and Studies
Canadian institutionsPolytechnique Montréal
FundersDivision of Chemical, Bioengineering, Environmental, and Transport SystemsNational Institute of Environmental Health SciencesPolytechnique MontréalPurdue UniversityU.S. Environmental Protection AgencyNational Science Foundation
KeywordsScope (computer science)Work (physics)BusinessGovernment (linguistics)Best practiceRemedial educationEconomic stagnationCoronavirus disease 2019 (COVID-19)Environmental planningQuality (philosophy)Risk analysis (engineering)EngineeringEnvironmental scienceComputer sciencePolitical scienceInfectious disease (medical specialty)MedicinePolitics

Abstract

fetched live from OpenAlex

The unprecedented number of building closures related to the coronavirus disease (COVID-19) pandemic is concerning because water stagnation will occur in many buildings that do not have water management plans in place. Stagnant water can have chemical and microbiological contaminants that pose potential health risks to occupants. Health officials, building owners, utilities, and other entities are rapidly developing guidance to address this issue, but the scope, applicability, and details included in the guidance vary widely. To provide a primer of large building water system preventative and remedial strategies, peer-reviewed, government, industry, and nonprofit literature relevant to water stagnation and decontamination practices for plumbing was synthesized. Preventative practices to help avoid the need for recommissioning (e.g., routine flushing) and specific actions, challenges, and limitations associated with recommissioning were identified and characterized. Considerations for worker and occupant safety were also indicated. The intended audience of this work includes organizations developing guidance.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Review
Teacher disagreement score0.986
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.194
GPT teacher head0.387
Teacher spread0.193 · 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