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Record W2365948571

Deliveries of Tar, Nicotine and CO in Mainstream Cigarette Smoke Under Health Canada Smoking Regime

2013· article· en· W2365948571 on OpenAlexaboutno aff
HU Qixi

Bibliographic record

VenueTobacco Science & Technology · 2013
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
Keywordstar (computing)NicotineSmokeCigarette smokeSidestream smokeCarbon monoxideWaste managementChemistryEnvironmental scienceMedicineEngineeringEnvironmental healthComputer scienceOrganic chemistryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

In order to investigate the influence of Canadian Intense smoking regime(HCI) on the deliveries of tar,nicotine(nic) and carbon monoxide(CO) in mainstream cigarette smoke, a collaborative study involving 18smoking machines in 12 laboratories were carried out by smoking 10 cigarette samples under ISO and HCI smoking regimes respectively. The results demonstrated that: 1) The deliveries of total particulate matters(TPM), tar, nic,CO, and moisture content under HCI smoking regime were much more higher than those under ISO smoking regime, and the ratios of HCI and ISO deliveries of the same components increased with the decrease of tar delivery determined under ISO regime. 2) The ratios of HCI and ISO deliveries of tar, nic and CO were similar,TPM ratio was slightly higher, while the moisture content significantly raised under HCI regime. 3) The ratios of HCI and ISO deliveries of tar, nic and CO augmented with the increase of ventilation rate of cigarette filter.4) Comparing with rotary smoking machine, linear smoking machine gave higher tar delivery, lower CO delivery, and similar nicotine delivery. 5) The determined results for 1R5F and CM6 in this study demonstrated better agreement with their reference values and the results by relevant international collaborative studies.

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 score0.218
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.282
Teacher spread0.264 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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