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Record W7018529814

Determining coefficients for mass-transfer models for volatile organic compound emissions from architectural coatings

2003· article· en· W7018529814 on OpenAlexfundvenueno aff

Bibliographic record

VenueNPARC · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
FundersNatural Resources CanadaNational Institute of Standards and TechnologyPublic Works and Government Services CanadaSyracuse UniversityU.S. Environmental Protection Agency
KeywordsEvaporationDiffusionVolatile organic compoundVapor pressureCoatingOrganic compoundAtmospheric pressure
DOInot available

Abstract

fetched live from OpenAlex

This research is to develop a mass-transfer model for describing the emission of volatile organic compounds (VOCs) from architectural coatings, which accounts for both surface evaporation and internal diffusion during the drying period. To apply this model, it is necessary to know the evaporation and diffusion coefficients of VOC emitted from the coating materials. An experimental method was, therefore, developed to determine both the evaporation and diffusion coefficients for six aliphatic hydrocarbons and six aromatic hydrocarbons from oil-based paint. It was shown that diffusion coefficients are inversely proportional to molecular weight, while evaporation coefficients are proportional to vapour pressure of the VOCs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2003
Admission routes2
Has abstractyes

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