Constituents of smoke from cigarettes made from diverted nicotine replacement therapy patches
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Anecdotes of nicotine replacement therapy patch misuse associated with the introduction of smoke-free prisons have been reported by media internationally, including Canada in 2006, New Zealand in 2011 and Australia in 2014. This study identifies chemical compounds released through diverted nicotine replacement therapy patches when they are smoked. DESIGN AND METHODS: Two samples were produced: (i) shredded 21 mg nicotine replacement therapy patches rolled with tea leaves into a cigarette; and (ii) patches boiled in water and tea leaves, and then dried tea leaves rolled into a cigarette. The smoke was tested for nicotine, caffeine and toxins. High-performance liquid chromatography, mass spectrometry and spectrophotometry were used to detect the presence and quantity of nicotine and caffeine. A specialised laboratory was contracted to test the presence of toxins. RESULTS: Nicotine was liberated when the two samples were burnt but not if the nicotine replacement therapy patches were boiled in water alone. High concentrations of formaldehyde, acetaldehyde, acrolein, toluene, xylene and heavy metals were also released. DISCUSSION AND CONCLUSION: Nicotine is released when diverted nicotine replacement therapy patches are smoked, as are caffeine and harmful toxins. These toxins have the potential to cause short- and long-term health damage.
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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) | 0.000 | 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".