What should every dental health professional know about electronic cigarettes?
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
Electronic cigarettes (E-cigarettes) have become increasingly popular around the world. Currently, dental professionals' knowledge and attitudes are varied with many clinicians unclear regarding the impact of E-cigarette products on the oral and general health of their patients. With developing social and health-related challenges, advice of dental and medical associations and other regulatory bodies on E-cigarette use is changing. Growing evidence demonstrating the risks of E-cigarette usage has prompted a review of legislation in the United Kingdom (UK), United States of America (USA), Australia and Canada to include the sale and availability of E-cigarettes, particularly those containing nicotine. Further consideration within the scientific and public health community is being given to assessing demographic usage patterns particularly uptake by non-smokers and adolescents, efficacy as a cessation tool, the impact of vapour on bystanders and direct injuries via explosions as well as emerging lung injuries. This article aims to provide a summary of the most up to date evidence relating to E-cigarette use, the latest position of dental associations and the oral health implications of E-cigarettes compared to conventional smoking. The article also aims to collate this information in order to provide dental clinicians with guidance on how to advise patients, specifically in answering common questions posed regarding E-cigarette use.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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