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Record W7108206453 · doi:10.25504/fairsharing.c12e1f

FAIRsharing record for: CANUE Data Portal

2025· dataset· W7108206453 on OpenAlexaboutno aff

Bibliographic record

VenueFAIRsharing.org · 2025
Typedataset
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental dataHuman healthSocioeconomic statusHealth dataData collectionUrban area

Abstract

fetched live from OpenAlex

This FAIRsharing record describes: CANUE (Canadian Urban Environmental Health Research Consortium) provides standardized, postal-code level environmental exposure data across Canada. The database includes air pollution, green and blue spaces, weather and climate, as well as urban and socioeconomic indicators. Its purpose is to link these data with health research to better understand how urban environments affect human health.

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)0.005
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0060.007
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0040.003
Science and technology studies0.0030.001
Scholarly communication0.0020.004
Open science0.0280.048
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0080.012

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 head0.109
GPT teacher head0.360
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; both teacher heads agree on what is shown here.

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
Published2025
Admission routes1
Has abstractyes

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