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Record W1020036629 · doi:10.2478/cttr-2014-0015

Filtration and Retention Characteristics of Smoke Components in Filters

2014· article· en· W1020036629 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBeiträge zur Tabakforschung international · 2014
Typearticle
Languageen
FieldEngineering
TopicFire Detection and Safety Systems
Canadian institutionsnot available
Fundersnot available
KeywordsFiltration (mathematics)SmokeChemistryPhenolTurbiditySidestream smokeChromatographyAnalytical Chemistry (journal)MathematicsOrganic chemistryStatistics

Abstract

fetched live from OpenAlex

SUMMARY The filtration and retention characteristics of nicotine, phenol, benzo[a]pyrene (B[a]P), 4-(methylnitrosamino)-1- (3-pyridyl)-1-butanone (NNK), crotonaldehyde, hydrogen cyanide (HCN) and ammonia in conventional cellulose acetate fiber filters were investigated. By quantitatively analyzing their contents released in mainstream smoke and retained in filters, their filtration efficiencies, taken as the ratio of filter retention content to total yield, were determined under both International Organization for Standardization (ISO) and Health Canadian Intense (HCI) smoking regimes. Using a precision laser cutter, the filters were either cut transversely into 5-7 segments for longitudinal distribution pattern study, or cut transversely into 3 segments firstly and then each segment was cut concentrically into 3 concentric segments for spatial distribution pattern study. Contents of the named smoke components retained in these filter segments were quantitatively analyzed. The data were calibrated and then processed with interpolation analysis and polynomial fitting. The longitudinal distribution patterns for all components mentioned above, as well as spatial distribution patterns for nicotine, phenol, HCN, ammonia and crotonaldehyde, were obtained. The filtration efficiencies of different smoke components varied between 24% and 15% for HCN, 87% and 92% for phenol under ISO and HCI smoking regimes respectively. The filtration efficiencies of all the studied components under HCI smoking were lower than under ISO smoking to different extents except phenol which showed the opposite trend. Different mainstream smoke components have their own retention behavior and distribution characteristics which are determined by the physical and chemical properties of the component and its interaction with cellulose acetate fiber and the glycerol triacetate within the filter. The diversity of retention distribution patterns of different components shows the high complexity of cigarette smoke filtration in filters. [Beitr. Tabakforsch Int. 26 (2014) 121-131]

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.423

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 head0.018
GPT teacher head0.207
Teacher spread0.190 · 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