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Record W4297502054 · doi:10.1126/sciadv.abo3381

How low can you go? Air pollution affects mortality at very low levels

2022· article· en· W4297502054 on OpenAlexaff
Scott Weichenthal, Lauren Pinault, Tanya Christidis, Richard T. Burnett, Jeffrey R. Brook, Yen Li Chu, Dan L. Crouse, Anders C. Erickson, Perry Hystad, Chi Li, Randall V. Martin, Jun Meng, Amanda J. Pappin, Michael Tjepkema, Aaron van Donkelaar, Crystal Weagle, Michael Bräuer

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsEnvironment and Climate Change CanadaDalhousie UniversityUniversity of TorontoMcGill UniversityStatistics CanadaUniversity of British ColumbiaHealth Canada
Fundersnot available
KeywordsAir pollutionEnvironmental healthEnvironmental scienceParticulatesPollutionParticulate pollutionGuidelinePopulationRange (aeronautics)GeographyMedicineBiologyEcologyEngineering

Abstract

fetched live from OpenAlex

The World Health Organization (WHO) recently released new guidelines for outdoor fine particulate air pollution (PM 2.5 ) recommending an annual average concentration of 5 μg/m 3 . Yet, our understanding of the concentration-response relationship between outdoor PM 2.5 and mortality in this range of near-background concentrations remains incomplete. To address this uncertainty, we conducted a population-based cohort study of 7.1 million adults in one of the world’s lowest exposure environments. Our findings reveal a supralinear concentration-response relationship between outdoor PM 2.5 and mortality at very low (<5 μg/m 3 ) concentrations. Our updated global concentration-response function incorporating this new information suggests an additional 1.5 million deaths globally attributable to outdoor PM 2.5 annually compared to previous estimates. The global health benefits of meeting the new WHO guideline for outdoor PM 2.5 are greater than previously assumed and indicate a need for continued reductions in outdoor air pollution around the world.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.003

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 head0.038
GPT teacher head0.320
Teacher spread0.281 · 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
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

Citations142
Published2022
Admission routes1
Has abstractyes

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