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Record W2148822217 · doi:10.1007/s00038-015-0690-y

Quantifying the health impacts of ambient air pollutants: recommendations of a WHO/Europe project

2015· article· en· W2148822217 on OpenAlexaff
Marie-Ève Héroux, H Ross Anderson, Richard Atkinson, Bert Brunekreef, Aaron Cohen, Francesco Forastiere, Fintan Hurley, Klea Katsouyanni, Daniel Krewski, Michał Krzyżanowski, Nino Künzli, Inga Mills, Xavier Querol, Bart Ostro, Heather Walton

Bibliographic record

VenueInternational Journal of Public Health · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of Ottawa
FundersEuropean CommissionWorld Health Organization
KeywordsAir pollutionAir quality indexEnvironmental healthEuropean unionHealth impact assessmentPublic healthParticulatesEnvironmental planningPollutantPollutionEnvironmental scienceBaseline (sea)Environmental resource managementBusinessEnvironmental protectionMedicineGeographyMeteorologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: Quantitative estimates of air pollution health impacts have become an increasingly critical input to policy decisions. The WHO project "Health risks of air pollution in Europe--HRAPIE" was implemented to provide the evidence-based concentration-response functions for quantifying air pollution health impacts to support the 2013 revision of the air quality policy for the European Union (EU). METHODS: A group of experts convened by WHO Regional Office for Europe reviewed the accumulated primary research evidence together with some commissioned reviews and recommended concentration-response functions for air pollutant-health outcome pairs for which there was sufficient evidence for a causal association. RESULTS: The concentration-response functions link several indicators of mortality and morbidity with short- and long-term exposure to particulate matter, ozone and nitrogen dioxide. The project also provides guidance on the use of these functions and associated baseline health information in the cost-benefit analysis. CONCLUSIONS: The project results provide the scientific basis for formulating policy actions to improve air quality and thereby reduce the burden of disease associated with air pollution in Europe.

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)0.009
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.280
GPT teacher head0.453
Teacher spread0.173 · 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

Citations296
Published2015
Admission routes1
Has abstractyes

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