Presence of nicotine in marketed nicotine-free e-liquids for electronic cigarettes
Bibliographic record
Abstract
Background and Purpose: Ever since the electronic cigarette made its debut in the market, it has been garnering great popularity due to public perception of it being a safer alternative to conventional cigarette. As a result, aside from being utilized in tobacco cessation programs, susceptible populations such as teenagers are slowly adopting this new trend of recreational E-cigarette smoking or “vaping”. The literature review conducted suggests that not only do different E-cigarette models exhibit different delivery efficiencies regarding percentage nicotine vapourization, there are discrepancies between what is labelled by the manufacturer and the actual nicotine content in the electronic cigarette liquids. This has serious public health implications because nicotine is the active chemical component in inducing addiction in cigarettes. As a result, recreational electronic cigarette users such as teenagers, may unknowingly become exposed to improper levels of nicotine, leading to a higher probability of nicotine dependence or switching to conventional smoking. The purpose of this study was to determine whether presence of nicotine can be detected in marketed nicotine-free electronic cigarette liquids. Methods: The nicotine content in electronic cigarette liquids was isolated and determined using Gas Chromatography Mass Spectrometry. Descriptive and inferential statistics was conducted using NCSS11 to see if there was a statistically significant difference between the labelled concentration of 0 mg in marketed “nicotine-free” electronic cigarettes from two popular brands, VapeWild and Mt Baker Vapour, to determine whether one brand has better quality control for nicotine content in nicotine-free E-liquids compared to the other brand. Results: Based on the analyzed E-liquid samples from the two brands, no nicotine was detected. Conclusion: E-cigarettes can be putatively considered as a safer alternative to conventional cigarettes because nicotine levels can be pre-determined and limited with a high degree of confidence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".