MétaCan
Menu
Back to cohort
Record W2030492249 · doi:10.1155/2013/846297

Remarks on Ambient Air Pollution and Health Outcomes

2013· article· en· W2030492249 on OpenAlexaff
Mieczysław Szyszkowicz

Bibliographic record

VenueISRN Public Health · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHealth Canada
Fundersnot available
KeywordsInterquartile rangeAir pollutionEnvironmental healthMedicineOdds ratioConditional logistic regressionPollutantAir pollutantsLogistic regressionEmergency departmentConfidence intervalAir pollutant concentrationsOddsPollutionInternal medicine

Abstract

fetched live from OpenAlex

Background . Ambient air pollution is a recognized risk factor for multiple health conditions. For some health problems, the impact of air pollution is particularly evident to the patients in a specific age range. Nonsimultaneous exposures to two or more air pollutants may have different relationships with health outcomes than do simultaneous exposures. Methods . Case-crossover technique was used to analyze data on emergency department (ED) visits for ischemic heart disease (IHD), epistaxis, and upper respiratory infection (URI). Conditional logistic regression models were used to estimate odds ratios and their 95% confidence intervals corresponding to an increase in an interquartile range of air pollutant concentrations. Results . The results for IHD show that for older patients (age 60+ years), the association between sulphur dioxide (SO 2 ) exposure and IHD is weak. For ED visits for epistaxis (O 3 and SO 2 in one model) and URI (O 3 and NO 2 in one model), air pollutants lagged differently in the common model indicated significant statistical associations but not for common lags. Conclusion . The study findings, based on analyzed examples, suggest that (i) IHD cases in older age are less related to air pollution and (ii) air pollutants may affect some health conditions by a specific sequence of exposure occurrences.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.725
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.081
GPT teacher head0.351
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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreCommentary

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

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueISRN Public HealthSame topicAir Quality and Health ImpactsFrench-language works237,207