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Record W2934048093 · doi:10.21037/tlcr.2019.03.08

Electronic cigarettes: not evidence-based cessation

2019· editorial· en· W2934048093 on OpenAlexaff
Alison Wallace, Robert Foronjy

Bibliographic record

VenueTranslational Lung Cancer Research · 2019
Typeeditorial
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of TorontoToronto General Hospital
FundersInternational Association for the Study of Lung Cancer
KeywordsMedicineSurgeon generalSmokeCigarette smokeElectronic cigaretteNicotineTobacco smokeEnvironmental healthPublic healthPsychiatryWaste managementPathologyEngineering

Abstract

fetched live from OpenAlex

Despite extensive efforts, smoking remains a modern-day epidemic with profound health consequences. In 1984, Dr. C. Everett Koop, the Surgeon General of the US at that time, presented an important speech on the hazards of smoking. In his speech he stated "The ultimate goal should be a smoke-free society by the year 2000." Unfortunately, we did not achieved that goal. Shortly after the target date for a smoke-free society as proposed by Dr. Koop, a new product was successfully introduced to the world, electronic cigarettes, or e-cigarettes, with the plan to provide a healthier alternative to smoking burnt tobacco. Unlike combustible cigarettes, e-cigarettes are battery-operated and use a heating element to heat an e-liquid releasing a chemical-filled aerosol. E-cigarettes also include e-pens, e-pipes, e-hookah, and e-cigars and are collectively known as electronic nicotine delivery systems (ENDS).

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 imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.018
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0080.008
Open science0.0050.002
Research integrity0.0180.042
Insufficient payload (model declined to judge)0.0090.010

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 head0.101
GPT teacher head0.458
Teacher spread0.357 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations23
Published2019
Admission routes1
Has abstractyes

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