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Record W1905082510 · doi:10.1071/wf15034

Wildfire smoke and public health risk

2015· article· en· W1905082510 on OpenAlexaff
Fabienne Reisen, Sandra M. Durán, Mike Flannigan, Catherine Elliott, Karen Rideout

Bibliographic record

VenueInternational Journal of Wildland Fire · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsBC Centre for Disease ControlUniversity of British ColumbiaUniversity of Alberta
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsSmokeAir quality indexEnvironmental sciencePublic healthClimate changeEnvironmental healthFire regimeHuman healthEnvironmental planningGeographyMediterranean climateVegetation (pathology)MeteorologyEnvironmental resource managementEcologyEcosystemMedicineBiology

Abstract

fetched live from OpenAlex

Wildfire activity is predicted to increase with global climate change, resulting in longer fire seasons and larger areas burned. The emissions from fires are highly variable owing to differences in fuel, burning conditions and other external environmental factors. The smoke that is generated can impact human populations spread over vast geographical areas. Wildfire smoke is a complex mixture of pollutants that can undergo physical and chemical transformation processes during transport and can have major impacts on air quality and public health. This review looks at the main features of smoke that should be considered in the assessment of public health risk. It describes the current state of knowledge and discusses how smoke is produced, what factors affect emissions and smoke distribution, and what constituents of smoke are most likely to cause adverse health effects.

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)0.001
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 score0.312
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.027
GPT teacher head0.270
Teacher spread0.242 · 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 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

Citations153
Published2015
Admission routes1
Has abstractyes

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