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Record W6931615718 · doi:10.5683/sp3/zpfxz2

Canadian Tobacco, Alcohol and Drugs Survey, 2017: Person file

2023· dataset· en· W6931615718 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2023
Typedataset
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsAlcoholPopulationAddictionPublic healthDrugData collectionPopulation health

Abstract

fetched live from OpenAlex

The Canadian Tobacco, Alcohol and Drugs Survey (CTADS) is a biennial general population survey of tobacco, alcohol and drug use among Canadians aged 15 years and older. It replaces the Canadian Tobacco Use Monitoring Survey (CTUMS), which was conducted from 1999 to 2012, and the Canadian Alcohol and Drug Use Monitoring Survey (CADUMS), which was conducted from 2008 to 2012. The CTADS merged the core tobacco content from CTUMS and the core drug and alcohol content from CADUMS, resulting in more efficient data collection and providing a tool to monitor and compare the use of multiple products and substances with addictive properties. The CTADS is conducted by Statistics Canada on behalf of Health 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)0.001
metaresearch head score (Gemma)0.010
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: Dataset
Teacher disagreement score0.067
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.015
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0450.033

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 head0.035
GPT teacher head0.286
Teacher spread0.251 · 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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