Bibliographic record
Abstract
Since its invention in 2003, electronic cigarettes’ (EC) users have been growing worldwide. ECs were first introduced in the market in Canada in 2004, and they remained illegal until 2018. ECs were initially marketed as a safer and cleaner alternative for the traditional combustible smoking and smoking cessation measures. Statistics show that EC use prevalence is the highest among the youths (15–19) and adolescents (20–24) years of age. EC has to promote cessation as it supplies nicotine to smokers prevent nicotine withdrawal syndrome and reduce motivation to continue smoking. EC use becomes a gateway to tobacco use and nicotine addiction. Nicotine exposure to youth and adolescents can damage the developing brain. EC use is also associated with an increased heart attack rate and other health problems. There are various reasons for using ECs, such as curiosity, quitting combustible smoking, or cutting down the number of cigarette use. Many people start ECs use before the age of 19 years. Majority of vapers like fruit flavor. Dual combustible cigarette smoking and EC use is a burning issue globally, including in Canada.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".