Bibliographic record
Abstract
Summary Electronic cigarettes (e-cigs) provide a smoke-free alternative for inhalation of nicotine without the vast array of toxic and carcinogenic combustion products produced by tobacco smoke. Elevated levels of toxic carbonyls may be generated during vaporisation; however, it is unclear whether that is indicative of a fault with the device or is due to the applied conditions of the test. A device, designed and built at this facility, was tested to determine the levels of selected toxic carbonyls. The reservoir was filled with approximately 960 mg of an e-liquid formulation containing 1.8% (w/v) nicotine. Devices were puffed 200 times in blocks of 40 using a standardised regime consisting of a 55 mL puff volume; 3 s puff duration; 30 s puff interval; square wave puff profile. Confirmatory testing for nicotine and total aerosol delivery resulted in mean (n = 8) values of 10 mg (RSD 12.3%) and 716 mg (RSD 11.2%), respectively. Emissions of toxic carbonyls were highly variable yet were between < 0.1% and 22.9% of expected levels from a Kentucky Reference Cigarette (K3R4F) puffed 200 times under Health Canada Intense smoking conditions. It has been shown that a device built to a high specification with relatively consistent nicotine and aerosol delivery emits inconsistent levels of carbonyls. The exposure is greatly reduced when compared with lit tobacco products. However, it was observed that as the reservoirs neared depletion then emission levels were significantly higher
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".