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Record W1965501521 · doi:10.3917/spub.054.0519

Baisse du tabagisme des élèves parisiens suite au plan cancer

2005· article· fr· W1965501521 on OpenAlexaboutno aff
Bertrand Dautzenberg, P Birkui, Jesús Sánchez Rubal, Lionel Riou França, Pradoura Duflot

Bibliographic record

VenueSanté Publique · 2005
Typearticle
Languagefr
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsTobacco useMedicineEnvironmental healthQuitlineCancer preventionDemographySuiteCancerQuarter (Canadian coin)Smoking preventionGerontologySmoking cessationPublic healthPopulationPolitical scienceGeographyNursing

Abstract

fetched live from OpenAlex

UNLABELLED: The French national cancer prevention plan launched in 2003 led many smokers to quit; however, no data is available on the rates of French adolescents who have begun smoking. METHOD: Every year since 1991, the Paris without Tobacco (PST) organisation carries out a cross-sectional survey among Parisian teenagers. The data from 2003-2004 have been compared with data from years prior to the implementation of the cancer prevention plan. RESULTS: Of a total of 54,781 youth questioned, quasi-stability in tobacco consumption (4%) was observed. Tobacco consumption has dramatically decreased since the launch of the national cancer plan: - 80% in 12-13 year olds, - 61% in 14-15 year olds, and - 55% in 16-17 year olds. This drop is linked to the decrease in numbers of adolescents who start to smoke before the age of 16. After 16 years of age, one-quarter of this decrease is explained and accounted for by the increase in the rate of ex-smokers. CONCLUSIONS: There are numerous reasons available to elucidate this rapid "denormalisation" of tobacco and smoking in general. The data testify to the success of the establishment and implementation of tobacco prevention campaigns and interventions called for within the framework of the National Cancer Plan.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.313
Teacher spread0.288 · 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

Citations3
Published2005
Admission routes1
Has abstractyes

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