Vaping linked with severe lung illnesses.
Bibliographic record
Abstract
“Vaping” refers to the use of an electronic device (e-cigarette, vape, vape-pen, etc.) with a heating element that, when activated, vaporizes a liquid so that the user of the device can inhale the vapour. The liquid, made for this purpose and commonly called an “e-liquid,” contains solvents, additives, water, flavourings and diverse active ingredients, usually liquid nicotine or cannabinoids, such as THC and CBD,* suspended in oils. The vapours, when inhaled by the person who vapes, produces psychoactive effects. While nicotine and cannabinoids are the most common psychoactive drugs consumed through vaping (Jones, Hill, Pardini, & Meier, 2016; Tucker et al., 2019), recent evidence shows that e-cigarettes can also be used as a way to deliver other non-medical psychotropic substances, such as methamphetamine and heroin (Breitbarth, Morgan, & Jones, 2018; Krakowiak, Poklis, & Peace, 2019). \n \nEarlier studies suggested that vaping nicotine is less harmful to the lungs and respiratory system than cigarette smoking (National Academies of Sciences, Engineering, and Medicine, 2018), and consequently vaping has emerged as a common method of inhaling nicotine and cannabinoids. According to the 2017 Canadian Tobacco, Alcohol and Drugs Survey, 15% of Canadians in the general population (aged 15 years and older) reported using an e-cigarette in their life, which represents a significant increase from the 13% reported in 2015 (Statistics Canada, 2017). \n \nEven more concerning is the popularity of vaping among youth and this is a trend that appears to be steadily growing. According to the most recent data obtained by the Youth Tobacco and Vaping Survey of the International Tobacco Control Policy Evaluation Project, 37% of Canadians aged 16 to 19 years old reported lifetime use of a nicotine e-cigarette in 2018, which represents a significant increase from the 29.3% reported in 2017 (Hammond et al., 2019). Vaping has also become a common way of inhaling cannabis among Canadians, with 29% of cannabis-using individuals (aged 15 years and older) indicating that vaping is their preferred method for cannabis use (Statistics Canada, 2017).
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".