Differences in cadmium transfer from tobacco to cigarette smoke, compared to arsenic or lead
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Arsenic, cadmium and lead levels in tobacco filler and cigarette smoke were determined in a 568-sample worldwide survey. Median tobacco levels for arsenic, cadmium and lead were 237, 769 and 397 ng/g respectively, comparable to those previously reported albeit somewhat lower for lead and cadmium. Median mainstream smoke yields for arsenic, cadmium and lead were <3.75, 18.2, and <12.8 ng/cig. under ISO, and <8.71, 75.1 and <45.7 ng/cig. under Health Canada Intense (HCI) smoking regime respectively. In the case of cigarettes with activated carbon, a selective retention of cadmium but not lead or arsenic was observed. This effect was more pronounced under ISO than under HCI smoking regimes. Cadmium selective retention by activated carbon was confirmed by testing specially designed prototype cigarettes and the causes for this selective filtration were investigated. The differences between cadmium, arsenic and lead in terms of their speciation in tobaccos and in cigarette smoke could be related to their distribution in the ash, butt, mainstream (in gas-phase and particulate-phase) and sidestream smoke of a smoked cigarette. The possible formation of organometallic cadmium derivatives in the smoke gas-phase is discussed, the presence of which could adequately explain the observed cadmium selective filtration.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.004 | 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 it