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Record W2592023458 · doi:10.1503/cmaj.109-5374

US calls for more restrictions on e-cigarettes for youth

2017· article· en· W2592023458 on OpenAlexvenueno aff
Jay Rankin

Bibliographic record

VenueCanadian Medical Association Journal · 2017
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsnot available
Fundersnot available
KeywordsSurgeon generalAddictionAction (physics)Preventive actionCall to actionMedicineCigarette smokingInternet privacyGerontologyPsychologyPsychiatryPublic healthAdvertisingComputer scienceComputer securityBusinessNursing

Abstract

fetched live from OpenAlex

E-cigarette use is “a major health concern” among youth, says the United States surgeon general in a call to action. In a [new report][1] on e-cigarette use among youth and young adults, Surgeon General Vivek H. Murthy states that youth are in danger of possible addiction and potential long-

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)0.005
metaresearch head score (Gemma)0.014
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.072
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0230.016
Insufficient payload (model declined to judge)0.0660.012

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 head0.054
GPT teacher head0.396
Teacher spread0.342 · 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
GenreCommentary

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

Citations0
Published2017
Admission routes1
Has abstractyes

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