Investigating predictability of in vitro toxicological assessments of cigarettes: Analysis of 7years of regulatory submissions to Canadian regulatory authorities
Bibliographic record
Abstract
A wealth of in vitro toxicological information on different types of tobaccos and tobacco products has been acquired and published, although the link between in vitro data and impact on human health remains elusive. The present study investigates the possibility of establishing quantitative models for the in vitro toxicological endpoint responses to cigarette smoke. To this end, it relies on information submitted to Canadian health authorities during the period 2006-2012. To our knowledge, this is the first time that published results concerning the influence of such factors as cigarette blend, diameter and filter type on in vitro toxicity are confirmed at the level of a representative range of products on a market. Taking these cigarette design features into account and adding a limited amount of quantitative mainstream smoke composition information, it is shown that, within the boundaries of the considered cigarette design parameters, the in vitro toxicological response can be effectively predicted. In vitro tests of tobacco products are an invaluable initial comparative product assessment tool. The present results reveal the limited value of data from repeated tests on products which do not undergo significant modifications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".