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Record W7133193243 · doi:10.1177/117863022110253

Air Pollution and Emergency Department Visits for Disease of the Genitourinary System

2021· article· en· W7133193243 on OpenAlexfundaboutno aff
Mieczysław Szyszkowicz, Stephanie Schoen, Nicholas de Angelis

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
FundersEnvironment and Climate Change Canada
KeywordsAir pollutionEmergency departmentAir quality indexHealth departmentPopulation healthPopulationAir Pollution IndexPublic health

Abstract

fetched live from OpenAlex

Health Canada is responsible for conducting risk assessments on air pollution as part of the Addressing Air Pollution Horizontal Initiative. There is growing evidence suggesting that air pollution can contribute to a large spectrum of health problems. Health Canada, carried out a study to examine whether air pollution concentration levels are associated with various health conditions. Admissions to emergency departments for all diseases of the genitourinary system were related to air pollution levels on the day of admission and in two weeks preceding admission. The study found that air pollutants, notably nitrogen dioxide and the air quality health index (AQHI), were associated with number of ED visit for the considered health problems, particularly for older females. The results suggest that ambient air pollutants may contribute to emergency department visits with various intensity considered by age, sex, and seasons. These data add to the body of knowledge used in assessing population health impacts and in identifying vulnerable sub-populations.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.815
Threshold uncertainty score0.372

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.011
GPT teacher head0.246
Teacher spread0.235 · 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 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

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaSame topicAir Quality and Health ImpactsFrench-language works237,207