Whither tobacco product regulation?: Table 1
Bibliographic record
Abstract
Despite decades of industry innovation and regulatory efforts, the harmfulness of conventional cigarettes has not changed. There are several pitfalls in this area, including the long time lag before health impacts of product regulatory changes become apparent, the danger of consumers deriving false reassurance of lesser harm in the interim period, the lack of relevant expertise and the lack of an internationally agreed and evidence-based strategic approach. Articles 9 and 10 of the Framework Convention on Tobacco Control provide the potential for such a global strategy, and knowledge and research has increased significantly over recent years. However, there are huge opportunity costs in implementing product disclosure and regulatory strategies: most national regulators have very limited human and financial resources, which should be focused on other evidence-based tobacco control interventions. We believe therefore that it is now time to abandon the notion of safe or safer cigarettes while moving consumers towards cleaner nicotine products as soon as possible. In parallel to this, we recommend a number of other strategies be implemented including: reducing the appeal of all tobacco products, forbidding new tobacco products or brand variants being marketed without evidence of reduced harm, appeal or addictiveness, and developing a tobacco industry resourced, but industry independent, Framework Convention on Tobacco Control global repository to assist national regulators in understanding and regulating the products on their markets.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.134 | 0.049 |
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".