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Record W1577858884 · doi:10.4271/2000-01-0663

The Contribution of Methanol (VOC) Emissions from Windshield Washer Fluid Use to the Formation of Ground-Level Ozone

2000· article· en· W1577858884 on OpenAlexaffabout
A. Carrière, Christine Kaufmann, Jerry L. Shapiro, P. Paine, J.H. Prinsen

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2000
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsWindshieldOzoneEnvironmental scienceMethanolWasherGround levelEnvironmental engineeringEnvironmental chemistryChemistryAtmospheric sciencesAerospace engineeringEngineeringGeologyArchitectural engineering

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">The potential for methanol emissions from the use of windshield washer fluid to contribute significantly to the formation of ground-level ozone in Canada is assessed. Reactivity and plausible chemical mechanisms for ozone formation are discussed. Assuming an environmental half-life of methanol of one month, a significant amount of these methanol emissions could participate in ozone formation. Options for reducing methanol emissions from this source were investigated in consultation with industry stakeholders. Recommendations included seasonal conversion to summer formulations, limiting methanol content, modifying OEM practices, and investigating more efficient fluid delivery systems.</div>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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 designBench or experimental
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

Citations4
Published2000
Admission routes2
Has abstractyes

Explore more

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