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Record W3048213147 · doi:10.29173/hsi292

The rise of electronic cigarettes

2020· article· en· W3048213147 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueHealth Science Inquiry · 2020
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPopularityAppealNicotineVariety (cybernetics)AdvertisingMedicineChemical constituentsEnvironmental healthPsychologyInternet privacyBusinessChemistryPsychiatryComputer sciencePolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Electronic cigarettes (ECs) have quickly gained popularity among adolescents and adults, and have begun to replace conventional cigarettes as a source of nicotine. Although little is known about the impact of the exposure of chemical constituents of ECs, two major constituents, propylene glycol and vegetable glycerin have been implicated as formaldehyde-releasing agents. The wide variety of EC flavours appeal to users of all ages with reports showing a positive correlation between EC use and sweet flavorings. In addition, although marketing strategies advertise ECs as tools to facilitate smoking cessation, the evidence supporting this role is weak. In terms of its effect on users with pre-existing cardiovascular diseases, the data is conflicting regarding whether ECs have an impact on cardiovascular function. Although it is obvious that their safety and efficacy needs to be better understood, it is nonetheless essential to review what the research conducted so far has shown.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.222

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.091
GPT teacher head0.393
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it