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Record W2036349570 · doi:10.1080/15287390590935897

Perspectives on Air Quality Policy Issues in Europe and North America

2005· article· en· W2036349570 on OpenAlexaffabout
Michał Krzyżanowski, John J. Vandenberg, Dave Stieb

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHealth Canada
Fundersnot available
KeywordsAir quality indexAgency (philosophy)Air pollutionEnvironmental planningEuropean commissionBusinessPublic healthParticulatesEnvironmental resource managementQuality (philosophy)Environmental protectionEnvironmental healthPolitical scienceEuropean unionEnvironmental scienceGeographyMedicineEconomic policy

Abstract

fetched live from OpenAlex

This article presents an overview of progress and future directions in air quality management in Europe, the United States, and Canada. The article describes the role of the European Commission, the Clean Air for Europe program, and the World Health Organization (WHO) in devising policies to reduce health risks due to air pollution in Europe. U.S. Environmental Protection Agency (EPA) standards for particulate matter (PM), air quality monitoring programs, and research efforts to support air quality management strategies are discussed. The unique aspects of air quality management in Canada are identified, including the need for a better understanding of the true burden of health effects and improved communication strategies to inform the public and stakeholders.

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)0.010
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.005
Science and technology studies0.0080.006
Scholarly communication0.0150.009
Open science0.0020.005
Research integrity0.0170.008
Insufficient payload (model declined to judge)0.0070.001

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 head0.034
GPT teacher head0.361
Teacher spread0.327 · 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 designTheoretical or conceptual
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

Citations13
Published2005
Admission routes2
Has abstractyes

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