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Record W2934048093 · doi:10.21037/tlcr.2019.03.08

Electronic cigarettes: not evidence-based cessation

2019· editorial· en· W2934048093 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.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.488
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.101
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