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Record W2021861597 · doi:10.1029/2004gl020093

Long‐range transport of Siberian biomass burning emissions and impact on surface ozone in western North America

2004· article· en· W2021861597 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeophysical Research Letters · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersOffice of Naval ResearchNational Aeronautics and Space AdministrationHarvard UniversityNational Science Foundation
KeywordsEnvironmental scienceBiomass burningAir quality indexOzoneRange (aeronautics)Atmospheric sciencesAerosolClimatologyPollutantChemical transport modelAir pollutionBiomass (ecology)MeteorologyGeographyOceanographyGeology

Abstract

fetched live from OpenAlex

During the summer of 2003, biomass fires burned a large area of Siberia, the largest in at least 10 years. We used the NRL Aerosol Analysis and Prediction System (NAAPS) model to forecast the transport of the smoke from these fires. Transport of these airmasses to North America was confirmed by aircraft and surface observations. The fires resulted in enhancements in summer background CO and O 3 of 23–37 and 5–9 ppbv, respectively, at 10 sites in Alaska, Canada and the Pacific Northwest. From the area burned, we estimate that the Siberian fires generated 68 Tg of CO and 0.82 Tg of NO x (as N). In addition, we show that the background O 3 enhancement contributed to an exceedance of the ozone air quality standard in the Pacific Northwest. These results show that regional air quality and health are linked to global processes, including climate, forest fires and long‐range transport of pollutants.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.024
GPT teacher head0.286
Teacher spread0.263 · 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