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Methanol exposure to car occupants from windshield washing fluid: a pilot study

2006· article· en· W2170381808 on OpenAlexaff
Adam Becalski, Karen H. Bartlett

Bibliographic record

VenueIndoor Air · 2006
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsUniversity of British ColumbiaHealth Canada
Fundersnot available
KeywordsWindshieldLibrary scienceOccupational hygieneHygieneOccupational safety and healthEnvironmental healthEngineeringMedicinePolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

UNLABELLED: Automobile occupants might be exposed to considerable amounts of methanol from previously unreported source, namely via the inhalation of vapors of winter-grade, methanol-based, windshield washing fluid that drains to the intake air ducts of the car. Air samples were collected in passenger cars during simulated operating conditions and analyzed for methanol via headspace gas chromatography-mass spectrometry, electron impact, selected ion monitoring. The method was linear in the 2-2000 ppm range. Concentrations exceeding 1000 ppm were recorded. PRACTICAL IMPLICATIONS: Using a winter-grade, methanol-based, windshield washing fluid for windshield cleaning in a passenger car can result in a methanol concentration in the air of the passenger cabin in excess of 1000 ppm. In view of the widespread use of this product, more studies are necessary to elucidate, in depth, the concentrations of methanol vapors which could be encountered in various weather and driving conditions as well as the concomitant contributing influences of car design. These studies are necessary to properly assess the hazards associated with use of the fluid and possible mitigation approaches which might include substitution of methanol by less toxic formulations.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.817

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 head0.023
GPT teacher head0.283
Teacher spread0.260 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2006
Admission routes1
Has abstractyes

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