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Record W2035290160 · doi:10.1080/152873901300343470

CHARACTERIZATION OF VOLATILE ORGANIC COMPOUNDS IN SMOKE AT MUNICIPAL STRUCTURAL FIRES

2001· article· en· W2035290160 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.

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2001
Typearticle
Languageen
FieldEngineering
TopicFire Detection and Safety Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsPropeneEthylbenzeneTolueneBenzeneStyreneEnvironmental chemistryChemistryNaphthaleneVolatile organic compoundGas chromatographyOrganic chemistryChromatographyCatalysis

Abstract

fetched live from OpenAlex

The objective of this study was to characterize volatile organic compounds (VOCs) found at municipal structural fires in order to identify sources of long-term health risks to firefighters, which may be contributing factors in heart disease and cancer. Firefighters collected air into evacuated Summa canisters inside burning buildings at nine municipal structural fires under conditions where they judged that at least some firefighters might remove their self-contained breathing apparatus masks. Volatile organic compounds were identified and quantified for 144 target compounds using cryogenic preconcentration and gas chromatography/mass spectral detection (GC/MSD) methodology operating in selected ion monitoring mode. Samples were also analyzed in SCAN mode and examined for the appearance of substances that were not present in the instrument standard calibration mixture. The spectra of municipal structural fires were surprisingly similar and remarkable for their simplicity, which was largely due to the dominating presence of benzene along with toluene and naphthalene. Propene and 1,3-butadiene were found in all of the fires, and styrene and other alkyl-substituted benzene compounds were frequently identified. Similar "fingerprints" of the same 14 substances (propene, benzene, xylenes, 1-butene/2-methylpropene, toluene, propane, 1,2-butadiene, 2-methylbutane, ethylbenzene, naphthalene, styrene, cyclopentene, 1-methylcyclopentene, isopropylbenzene) previously identified at experimental fires burning various solid combustible materials were also found at municipal structural fires, accounting for 76.8% of the total VOCs measured. Statistically significant positive correlations were found between increasing levels of benzene and levels of propene, the xylenes, toluene, 1-butene/2-methylpropene, 1,3-butadiene, and naphthalene. Given the toxicity/carcinogenicity of those VOCs that were found in the highest concentrations, particularly benzene, 1,3-butadiene, and styrene, further investigation of VOC exposures of firefighters is warranted. Benzene, or its metabolic product s-phenylmercapturic acid in urine, was identified as a suitable chemical marker for firefighter exposure to combustion products.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.011
GPT teacher head0.225
Teacher spread0.215 · 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