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Record W2609457795 · doi:10.1111/ina.12392

Human symptom responses to bioeffluents, short-chain carbonyls/acids, and long-chain carbonyls in a simulated aircraft cabin environment

2017· article· en· W2609457795 on OpenAlexaff
Clifford P. Weisel, Nancy Fiedler, Charles J. Weschler, Pamela Ohman‐Strickland, Krishnan R. Mohan, Kevin McNeil, David Space

Bibliographic record

VenueIndoor Air · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsBoeing (Canada)
FundersNational Institute of Environmental Health Sciences
KeywordsIrritationAir quality indexChemistryPollutantEnvironmental chemistryToxicologyMedicineOrganic chemistryBiologyEcology

Abstract

fetched live from OpenAlex

Occupants of aircraft have reported an array of symptoms related to general discomfort and irritation. Volatile organic compounds (VOCs) have been suggested to contribute to the reported symptoms. VOCs are from products used, bioeffluents from people and oxidation reaction products. Thirty-six healthy, young female subjects rated symptoms and environmental quality during an eight-hour exposure to groups of compounds often present in aircraft: (i) long-chain carbonyls, (ii) simulated bioeffluents, and (iii) short-chain carbonyls/organic acids. Statistically more symptoms were identified for the simulated bioeffluents and, to a lesser extent, short-chain carbonyls/organic acids compared to a control condition, although they remained in the acceptable range. There were three temporal patterns in the environmental quality and symptom reports: (i) an adaptive response (immediate increases followed by a decline); (ii) an apparent physiological effect (increases one to three hours into the exposure that remained elevated); and (iii) no statistical differences in reported environmental quality or symptom severity compared to the control air conditions. Typical concentrations found in aircraft can cause transitory symptoms in healthy individuals questioning the adequacy of current standards. Understanding the effects on individuals sensitive to air pollutants and methods to remove the compounds causing the greatest symptom responses are needed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.034
GPT teacher head0.319
Teacher spread0.285 · 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.

Study designObservational
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

Citations19
Published2017
Admission routes1
Has abstractyes

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