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Record W6926343067 · doi:10.25318/13250008-eng

Canadian Health Measures Survey, Cycle 1 Oral Health: Public Use Microdata File

2023· dataset· en· W6926343067 on OpenAlexaboutno aff

Bibliographic record

VenueStatistics Canada Dissemination · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMicrodata (statistics)Public healthPublic useOral healthPopulation healthHealth dataGeneral partnershipPopulationNational Health Interview Survey

Abstract

fetched live from OpenAlex

The Canadian Health Measures Survey (CHMS) Cycle 1 oral health public use microdata file (PUMF) is now available. The PUMF consists of 307 variables from the oral health examination completed as part the CHMS, a subset of variables present or recoded from the master file. Data was collected from 2007 to 2009 from approximately 6,000 people in 15 communities randomly selected across Canada and represents 97% of the Canadian population aged 6 to 79 years old. The Oral Health module of the CHMS is a result of a collaborative partnership between three federal departments: Statistics Canada, Health Canada and the Department of National Defence.

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)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.071
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.016
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0710.028

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 head0.067
GPT teacher head0.337
Teacher spread0.269 · 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 designObservational
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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Same venueStatistics Canada DisseminationFrench-language works237,207