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Record W2054644597 · doi:10.1177/1420326x0101000202

Development of a Method for Measuring Volatile Organic Compounds in the Blood of Fire Victims Using'Purge and Trap' Gas Chromatography

2001· article· en· W2054644597 on OpenAlex
Paul Houeto, Stephen W. Borron, Fabrice Marlière, Frédéric J. Baud, P. Levillain

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

VenueIndoor and Built Environment · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsInstitut universitaire en santé mentale de Montréal
Fundersnot available
KeywordsChromatographyGas chromatographySmoke inhalationFlame ionization detectorVolatile organic compoundSmokeRepeatabilityTrap (plumbing)Environmental chemistryChemistryPurgeGas chromatography–mass spectrometryEnvironmental scienceWaste managementMass spectrometryEnvironmental engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Smoke inhalation remains a major cause of morbidity and mortality. Clinical and laboratory studies have re vealed numerous potentially toxic components of com bustion in the fire environment and in human tissue samples. However, the frequency and importance of the various compounds remains poorly understood. A new simple method to quantitatively measure volatile or ganic compounds (VOCs) in small samples of the blood of fire victims has been developed utilising the 'purge and trap' method of gas phase chromatography with flame ionisation detection using two columns. Thirty- three compounds were identified on the basis of the retention index method with acceptable repeatability and reproducibility. This method should permit a more complete investigation of the toxic volatile organic com pounds found in fire victims.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.530

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 studies0.0000.000
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 head0.025
GPT teacher head0.248
Teacher spread0.223 · 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