MétaCan
Menu
Back to cohort

Sorptive Interactions between VOCs and Indoor Materials

2001· article· en· W2047143681 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

VenueIndoor Air · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCitationLibrary scienceComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This study was carried out using various materials (carpet, gypsum board, upholstery, vinyl and wood flooring, acoustic tiles, and fruit) that were exposed to eight gaseous volatile organic compounds (VOCs) (isopropanol, MTBE, cyclohexane, toluene, ethylbenzene, tetrachloroethene, 1,2-dichlorobenzene, and 1,2,4-trichlorobenzene) in electro-polished stainless-steel chambers. Dynamic responses in VOC concentrations were used to determine linear adsorption and desorption rate coefficients and equilibrium partition coefficients. A linear adsorption/desorption model was used to effectively describe the interactions between VOCs and indoor surface materials for short-term source events (10 h). Relationships between sorption parameters and chemical vapor pressure and the octanol-air partition coefficient were observed. Carpet was identified as the most significant sorptive sink for non-polar VOCs. Virgin gypsum board was observed to be a significant sink for highly polar VOCs. Sorptive interactions between non-polar VOCs and indoor materials were not affected by variations in relative humidity. However, increases in relative humidity were observed to increase the degree of sorption of isopropanol to carpet.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.999

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)0.0030.002

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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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