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Record W2066684918 · doi:10.1007/s11869-009-0027-1

Differential and combined impacts of extreme temperatures and air pollution on human mortality in south–central Canada. Part I: historical analysis

2008· article· en· W2066684918 on OpenAlex
Chad Shouquan Cheng, Monica Campbell, Qian Li, Guilong Li, Heather Auld, Nancy L. Day, David Pengelly, Sarah Gingrich, Joan Klaassen, Don MacIver, Neil Comer, Yang Mao, Wendy Thompson, Hong Lin

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAir Quality Atmosphere & Health · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsPublic Health Agency of CanadaImpactToronto Public HealthMcMaster UniversityEnvironment and Climate Change Canada
FundersHealth Canada
KeywordsAir pollutionEnvironmental sciencePollutionOzonePollutantParticulatesNitrogen dioxideAtmospheric sciencesMeteorologyEnvironmental healthGeographyEcologyMedicineBiology

Abstract

fetched live from OpenAlex

This paper forms the first part of an introduction to a synoptic weather typing approach to assess differential and combined impacts of extreme temperatures and air pollution on human mortality in south–central Canada, focusing on historical analysis (a companion paper—Part II focusing on future estimates). In this study, an automated synoptic weather typing procedure was used to identify weather types that have a marked association with high air pollution levels and temperature extremes, and facilitates assessments of the differential and combined health impacts of extreme temperatures and air pollution. Annual mean elevated mortality (when daily mortality exceeds the baseline) associated with extreme temperatures and acute exposures to air pollution, based on 1954–2000, was 1,082 [95% confidence interval (CI) of 1,017–1,147] for Montreal, 1,047 (CI 994–1,100) for Toronto, 462 (CI 438–486) for Ottawa, and 327 (CI 311–343) for Windsor. Of this annual mean elevated mortality, extreme temperatures are usually associated with roughly 20%, while air pollution is associated with the remaining 80%. Three pollutants (ozone, sulfur dioxide, and nitrogen dioxide) are associated with approximately 75% of total air pollution-related mortality across the study area. The remaining 25% is almost evenly associated with suspended particles and carbon monoxide, the other two pollutants addressed in this study. Of the five pollutants, ozone is most significantly associated with elevated mortality, making up one-third of the total air pollution-related mortality. PM 2.5 and PM 10 were not used as a measure of particulate in the study due to brief data records. The study results also suggest that, on the basis of daily mortality risks, extreme temperature-related weather presents a much greater risk to human health during heat waves and cold spells than air pollution. For example, in Montreal and Toronto, daily mean elevated mortality counts within the hottest weather type were twice as high as those within air pollution-related weather types.

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 score0.072
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.094
GPT teacher head0.329
Teacher spread0.236 · 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