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Record W2125008656 · doi:10.1093/ntr/nts137

Tobacco Use Among Southwestern Alaska Native People

2012· article· en· W2125008656 on OpenAlexaff
Caroline C. Renner, A Lanier, Bruce R. Lindgren, Jeffrey T. Jensen, Christi A. Patten, Mark Parascandola, Neal L. Benowitz, Rachel F. Tyndale, D. K. Hatsukami

Bibliographic record

VenueNicotine & Tobacco Research · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Cancer InstituteU.S. Public Health ServiceSubstance Abuse and Mental Health Services AdministrationCenters for Disease Control and Prevention
KeywordsLibrary scienceMedicineHistoryArt historyArtComputer science

Abstract

fetched live from OpenAlex

INTRODUCTION: We examined the characteristics, attitudes, beliefs, and exposure to tobacco products in a cohort of rural dwelling Alaska Native (AN) people. METHODS: We conducted a study of 400 of AN adult tobacco users and nonusers living in Southwestern Alaska. Questionnaires covered variables such as demographics, tobacco-use history, current tobacco use and dependence scales, general health status, attitudes and beliefs about tobacco, and quitting history. RESULTS: The study population smoked 7.8 cigarettes per day compared with 16.8 on average for the U.S. population: a significant proportion of the population engaged in dual use of cigarettes and smokeless tobacco products. Over one third (40.9%), first tried tobacco at age 11 or younger. The mean measures of tobacco addiction (e.g., Fagerstrom Test for Nicotine Dependence, Severson Scale of Smokeless Tobacco Dependence) scores were lower compared with other U.S. populations. CONCLUSIONS: Very high tobacco-use prevalence, dual product use, and early tobacco use are observed in Southwestern AN people. Unexpectedly these did not appear to be correlated with heavier individual tobacco use or higher levels of addiction in this population.

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 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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0060.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.007

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 head0.157
GPT teacher head0.459
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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations20
Published2012
Admission routes1
Has abstractyes

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