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Record W6907620704 · doi:10.25318/1310055401-eng

Body mass index (BMI), by age group and sex, household population aged 18 and over excluding pregnant women, Canada, provinces, territories, health regions (January 2000 boundaries) and peer groups

2020· dataset· en· W6907620704 on OpenAlexaboutno aff

Bibliographic record

VenueStatistics Canada Dissemination · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsUnderweightBody mass indexOverweightConfidence intervalPopulationObesityAge groupsTable (database)

Abstract

fetched live from OpenAlex

This table contains 558792 series, with data for years 2000 - 2000 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (not all combinations are available): Geography (199 items: Canada; Health and Community Services Eastern Region; Newfoundland and Labrador (Peer group D); Newfoundland and Labrador; Health and Community Services St. John's Region; Newfoundland and Labrador (Peer group H) ...), Age group (13 items: Total; 18 years and over; 18-34 years; 18-24 years; 18-19 years ...), Sex (3 items: Both sexes; Males; Females ...), Body mass index (BMI) (9 items: Total population for the variable body mass index; Overweight - BMI 25.0-29.9; Underweight - BMI under 18.5; Normal weight - BMI 18.5-24.9 ...), Characteristics (8 items: Number of persons; Coefficient of variation for number of persons; Low 95% confidence interval - number of persons; High 95% confidence interval - number of persons ...).

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)0.007
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 score0.135
Threshold uncertainty score0.271

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.017
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0490.034

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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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Same venueStatistics Canada DisseminationFrench-language works237,207