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Record W2530136340 · doi:10.9778/cmajo.20150069

Cancer incidence attributable to tobacco in Alberta, Canada, in 2012

2016· article· en· W2530136340 on OpenAlexaffvenueabout
Abbey E. Poirier, Anne Grundy, Farah Khandwala, Satu Tamminen, Christine M. Friedenreich, Darren R. Brenner

Bibliographic record

VenueCMAJ Open · 2016
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsMedicineTobacco smokeIncidence (geometry)CancerLung cancerAttributable riskPopulationEnvironmental healthPassive smokingTobacco useTobacco controlCancer registryDemographyPublic healthInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Strong and consistent epidemiologic evidence shows that tobacco smoking causes cancers at various sites. The purpose of this study was to quantify the proportion and total number of site-specific cancers in Alberta attributable to tobacco exposure. METHODS: The proportion of incident cancer cases attributable to active and passive tobacco exposure in Alberta was estimated with population attributable risks. Data from the Canadian Community Health Survey (CCHS) for 2000-2007 were used to estimate prevalence of active (current or former smoker) and passive (second-hand smoke) tobacco exposure in Alberta. RESULTS: According to the 2000/01 CCHS, 29.1% and 38.6% of Albertans were estimated to be current and former smokers, respectively. According to the 2003 CCHS, 23.7% of Albertans who had never smoked reported regular second-hand exposure to tobacco. Population attributable risk estimates for tobacco-related cancer sites ranged from about 4% for ovarian cancer to 74% for laryngeal cancer. About 5% of incident lung cancers in men and women who never smoked could be attributed to passive tobacco exposure. Overall, 37.0% of tobacco-related cancers in Alberta (or 15.7% of all cancers) were estimated to be attributable to active tobacco smoking in 2012. INTERPRETATION: A notable proportion of cancers associated with tobacco use were estimated to be attributable to active smoking in Alberta. Strategies to reduce the prevalence of active tobacco smoking in Alberta could have a considerable impact on future cancer incidence.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.335
Teacher spread0.297 · 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 teacher head, not a consensus.

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

Citations12
Published2016
Admission routes3
Has abstractyes

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