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Record W4400075366 · doi:10.1093/annweh/wxae035.144

137a - Breathe freely initiative to prevent occupational lung disease – Canadian and US rollout

2024· article· en· W4400075366 on OpenAlexaboutno aff
Jason McInnis

Bibliographic record

VenueAnnals of Work Exposures and Health · 2024
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational safety and healthOccupational lung diseaseMedicineEnvironmental healthOccupational exposureMedical emergencyPathology

Abstract

fetched live from OpenAlex

Abstract Breathe Freely is a British Occupational Hygiene Society (BOHS) initiative aimed at reducing occupational lung disease in the UK, which causes significant debilitating ill-health and an estimated 13,000 deaths per year in the UK. Breathe Freely is about raising awareness of both the problem and how to do something about it: we can protect workers’ health and prevent most of these diseases and deaths. It is not just “the right thing to do”, it is good for business as well. Broad acceptance of this fundamental concept is part of the solution. Thanks to the support and collaboration of the BOHS, both the AIHA construction committee (US) and CRBOH (Canada) have taken steps to introduce Breathe Freely in their respective countries. This session will delve into the core objectives of Breathe Freely and provide updates on its implementation progress in Canada and the United States.

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)0.010
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: Other · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.398

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.002
Scholarly communication0.0060.001
Open science0.0030.005
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0290.005

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 head0.075
GPT teacher head0.388
Teacher spread0.313 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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