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Record W2132325147 · doi:10.1093/toxsci/kft194

Tobacco Smoke–Related Health Effects Induced by 1,3-Butadiene and Strategies for Risk Reduction

2013· article· en· W2132325147 on OpenAlexaboutno aff
Lya G. Soeteman‐Hernández, Peter Bos, Reinskje Talhout

Bibliographic record

VenueToxicological Sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsSidestream smokeMedicineTobacco smokeEnvironmental healthToxicityNicotineTobacco industrySmokeToxicologyCancerCigarette smokePathologyInternal medicineChemistryBiology

Abstract

fetched live from OpenAlex

1,3-Butadiene (BD) is a smoke component selected by the World Health Organization (WHO) study group on Tobacco Product Regulation (TobReg) for mandated lowering. We examined the tobacco smoke-related health effects induced by BD and possible health impacts of risk reduction strategies. BD levels in mainstream smoke (MSS) from international and Canadian cigarettes and environmental tobacco smoke (ETS) were derived from scientific journals and international government reports. Dose-response analyses from toxicity studies from government reports were evaluated and the most sensitive cancer and noncancer endpoints were selected. The risks were evaluated by taking the ratio (margin of exposure, MOE) from the most sensitive toxicity endpoint and appropriate exposure estimates for BD in MSS and ETS. BD is a good choice for lowering given that MSS and ETS were at levels for cancer (leukemia) and noncancer (ovarian atrophy) risks, and the risks can be significantly lowered when lowering the BD concentrations in smoke. Several risk reduction strategies were analyzed including a maximum level of 125% of the median BD value per milligram nicotine obtained from international brands as recommended by the WHO TobReg, tobacco substitute sheets, dual and triple carbon filters, and polymer-derived carbon. The use of tobacco substitute sheet with a polymer-derived carbon filter resulted in the most significant change in risk for cancer and noncancer effects. Our results demonstrate that MOE analysis might be a practical way to assess the impact of risk reduction strategies on human health in the future.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.054
GPT teacher head0.350
Teacher spread0.296 · 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

Citations22
Published2013
Admission routes1
Has abstractyes

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