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Record W2170159546 · doi:10.1136/tc.2008.024778

Constituents in tobacco and smoke emissions from Canadian cigarettes

2008· article· en· W2170159546 on OpenAlexaffabout
David Hammond, Richard J. O’Connor

Bibliographic record

VenueTobacco Control · 2008
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Waterloo
FundersNational Cancer InstituteCancer Research UK
KeywordsSmokeTobacco smokeEnvironmental healthThird-hand smokeBusinessEnvironmental scienceAdvertisingFood scienceSidestream smokeMedicineChemistryCigarette smokeWaste managementEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: There is relatively little information available about the chemical constituents of tobacco and individual toxic emissions from cigarettes and other tobacco products. OBJECTIVE: To characterise 21 constituents in whole tobacco and 41 constituents in the smoke emissions of Canadian cigarettes, as well as to compare differences between domestic and imported brands. METHODS: All data were released as part of Canada's Tobacco Reporting Regulations. Data are reported for 247 brands tested in 2004. RESULTS: The results indicate significant differences in the constituent levels of domestic and imported cigarette tobacco. Levels of ammonia compounds were significantly higher in imported "US blended" tobacco compared to domestically manufactured brands. Toxic emissions for tobacco-specific nitrosamines were significantly higher for imported cigarettes under both the ISO and Canadian Intense testing methods; however domestic cigarettes had higher levels of other toxic constituents, including benzo[a]pyrene. The findings also highlight the extent to which nicotine, heavy metals and tobacco-specific nitrosamines are "transferred" from the whole tobacco to the smoke. CONCLUSIONS: The findings illustrate important differences between domestically manufactured Virginia flue-cured cigarettes and imported US blended cigarettes. Although the findings suggest that domestic cigarettes had lower levels of constituents such as ammonia, which are associated with increased "additives", Canadian cigarettes were by no means "additive-free." Overall, these findings provide important benchmarks for making historical and international comparisons across brands on key constituents.

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)0.000
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 score0.117
Threshold uncertainty score0.979

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 head0.025
GPT teacher head0.264
Teacher spread0.239 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations82
Published2008
Admission routes2
Has abstractyes

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