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Record W2951757173 · doi:10.1039/c9em00111e

Illuminating the dark side of indoor oxidants

2019· review· en· W2951757173 on OpenAlexaff
Cora J. Young, Shan Zhou, Jeffrey A. Siegel, Tara F. Kahan

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsUniversity of SaskatchewanPublic Health OntarioUniversity of TorontoYork University
FundersAlfred P. Sloan Foundation
KeywordsEnvironmental scienceEnvironmental chemistryChemistry

Abstract

fetched live from OpenAlex

The chemistry of oxidants and their precursors (oxidants*) plays a central role in outdoor environments but its importance in indoor air remains poorly understood. Ozone (O3) chemistry is important in some indoor environments and, until recently, ozone was thought to be the dominant oxidant indoors. There is now evidence that formation of the hydroxyl radical by photolysis of nitrous acid (HONO) and formaldehyde (HCHO) may be important indoors. In the past few years, high time-resolution measurements of oxidants* indoors have become more common and the importance of event-based release of oxidants* during activities such as cleaning has been proposed. Here we review the current understanding of oxidants* indoors, including drivers of the formation and loss of oxidants*, levels of oxidants* in indoor environments, and important directions for future research.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.028
GPT teacher head0.296
Teacher spread0.268 · 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

Citations70
Published2019
Admission routes1
Has abstractyes

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