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Record W2073577113 · doi:10.3155/1047-3289.60.10.1154

Multipollutant Air Quality Management

2010· article· en· W2073577113 on OpenAlex
Judith C. Chow, John Bachmann, John Kinsman, A.H. Legge, John G. Watson, George M. Hidy, William T. Pennell

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Air & Waste Management Association · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsCanadian Bio-Systems (Canada)
Fundersnot available
KeywordsAir quality indexCriteria air contaminantsAir pollutantsEnvironmental sciencePollutantRisk analysis (engineering)Air pollutionEnvironmental planningEnvironmental resource managementQuality (philosophy)BusinessEnvironmental protectionMeteorologyGeographyEcology

Abstract

fetched live from OpenAlex

Abstract On the basis of a recent NARSTO assessment, this review discusses the factors involved in the implementation of a risk- and results-based multipollutant air quality management strategy applicable to North America. Such a strategy could evolve from current single-pollutant regulatory practices using a series of steps that would seek to minimize risk of exposure for humans and ecosystems while providing for a quantitative evaluation of the effectiveness of the management process. The tools needed to support multipollutant air quality management are summarized. They include application of a formal risk analysis, accounting for atmospheric processes, ambient measurements, emissions characterization, air quality modeling of emissions to ambient concentrations, and characterization of human and ecological responses to ambient pollutant exposure. The new management strategy would expand the current practice of accountability that relates emission reductions and attainment of air quality derived from air...

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.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 science0.0010.000
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 head0.017
GPT teacher head0.286
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