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Record W6894340877 · doi:10.5683/sp3/ysvkwm

Enquête canadienne sur le tabac et la nicotine 2022

2023· dataset· fr· W6894340877 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2023
Typedataset
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCannabisGerman Federal RepublicStatistical analysisBinge drinking

Abstract

fetched live from OpenAlex

L'Enquête canadienne sur le tabac et la nicotine (ECTN) de 2022 permet de mesurer la prévalence de la consommation de cigarettes, de produits de vapotage, de cannabis et d'alcool chez les Canadiens âgés de 15 ans et plus. Cette enquête est menée par Statistique Canada pour le compte de Santé Canada. La compréhension des tendances canadiennes en matière de consommation de tabac, de nicotine, de cannabis, de produits de vapotage et d'alcool est essentielle à l'élaboration, à la mise en œuvre et à l'évaluation efficaces des stratégies, politiques et programmes nationaux et provinciaux. La compréhension des tendances canadiennes relatives à la consommation de tabac, de nicotine, de cannabis et d’alcool est essentielle à l’élaboration, à la mise en œuvre et à l’évaluation efficaces des stratégies, politiques et programmes nationaux et provinciaux. L’ECTN a été menée par Statistique Canada à la fin de 2022 et au début de 2023, avec la coopération et le soutien de Santé Canada.

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)0.014
metaresearch head score (Gemma)0.020
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: Dataset · Consensus signal: none
Teacher disagreement score0.279
Threshold uncertainty score0.561

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0050.002
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0320.009

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 head0.021
GPT teacher head0.262
Teacher spread0.241 · 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
GenreDataset

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
Published2023
Admission routes1
Has abstractyes

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