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Record W7054643401

Adsorption capacity of activated carbon for n-alkane VOCs

2000· article· en· W7054643401 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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueNPARC · 2000
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsNational Research Council Canada
FundersNatural Resources CanadaNational Research Council Canada
KeywordsActivated carbonAdsorptionIndoor air qualityVolatile organic compoundVentilation (architecture)
DOInot available

Abstract

fetched live from OpenAlex

The volatile organic compounds (VOCs) in the indoor air come from many sources including building materials, furnishings, occupant activities and in some cases, the ventilation air. Granular activated carbons (GAC) have been increasingly used to remove these contaminants, particularly for small commercial buildings and those located in urban centers or near industrial plants where the quality of outdoor air may be worse than that of the indoor air. Tests were conducted to determine the efficiency of GAC in removing VOCs from the indoor air. Seven n-alkanes VOCs covering a wide range of molecular sizes were selected for these tests. They were pentane, hexane, heptane, octane, nonane, decane, and undecane. The breakthrough time and VOC mass adsorbed on GAC for these individual VOCs were obtained. It was found that the adsorption capacity of GAC decreases as the initial VOC concentration, C0, decreases.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.243

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 head0.017
GPT teacher head0.210
Teacher spread0.193 · 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