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Record W4400075809 · doi:10.1093/annweh/wxae035.168

249b - A new respirator performance standard for Canada

2024· article· en· W4400075809 on OpenAlexaboutno aff
Simon Smith

Bibliographic record

VenueAnnals of Work Exposures and Health · 2024
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsnot available
Fundersnot available
KeywordsRespiratorEnvironmental healthMedical emergencyEnvironmental scienceMedicineMaterials science

Abstract

fetched live from OpenAlex

Abstract Canada has a complex regulatory structure for occupational health and safety with legislation and regulation split among thirteen regional bodies, plus the federal government. Details for implementation of respiratory protection programs are addressed in a national consensus standard, and for product performance approvals. Canada’s has historically accepted those from the US organisation, the National Institute for Occupational Safety and Health (NIOSH). During the Covid pandemic, many new respirator manufacturing operations started in Canada to address equipment shortages, but prioritization changes at NIOSH to support US requirements meant that the approval time for new Canadian products was of the order of months, exacerbating the supply crisis. The Canadian Government acted promptly to create an interim product approval structure, with the plan for a long-term solution for CSA Group (Canadian Standards Association) to build a new national respirator performance standard and certification system. Reflecting the urgency of the situation, this new Canadian standard was developed extremely rapidly over 2021 by a dedicated expert committee, incorporating performance requirements that balanced historic familiarity with new features reflecting the best of national and international standards. This new standard and an associated certification system administered by the CSA Group now supports an improved respiratory protective equipment supply chain, and is used in Canada in parallel with the existing NIOSH approval.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.101
GPT teacher head0.372
Teacher spread0.270 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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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