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Record W2914189509 · doi:10.1289/isee.2011.00936

LUNG INFLAMMATION AMONG CHILDREN WITH ASTHMA EXPOSED TO INDUSTRIAL AND TRAFFIC POLLUTION

2011· article· en· W2914189509 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

VenueISEE Conference Abstracts · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsMcGill UniversityInstitut National de Santé Publique du QuébecHealth Canada
Fundersnot available
KeywordsAsthmaExhaled nitric oxideAir pollutionMedicineEnvironmental healthParticulatesPollutantEnvironmental scienceSpirometryInternal medicineChemistry

Abstract

fetched live from OpenAlex

Background and Aims: Children with asthma are susceptible to the effects of ambient air pollution, including increased symptoms and lung inflammation. Industrial emissions are an important source of air pollution in many areas. Oil refinery emissions are of particular concern as they comprise a complex mixture of organic and inorganic pollutants. We examined associations between fractional exhaled nitric oxide (FeNO), an indicator of airway inflammation, and exposure to oil refinery and traffic emissions on the health of children with asthma in Montreal, Canada. Methods: We recruited 69 children (age 8-13 years) with a physician diagnosis of asthma from schools and an asthma clinic. Subjects participated in the panel study for 10 consecutive days between October 2009 and April 2010. We measured personal exposures to sulphur dioxide (SO2) using Ogawa passive samplers (Ogawa & Company, Pompano Beach, FL, USA) and fine particulate matter (PM2.5) using Harvard Personal Environmental Monitors (HPEM, BGI, MA, USA) and continuously using the personal DataRAM (pDR-1200, MIE Inc, Bedford, MA). Filters were also analyzed for metals associated with oil refinery emissions. We recorded online FeNO daily using the NIOX MINO monitor (Aerocrine, Solna, Sweden) and collected participants’ reports on health, medication use, and activities. Linear mixed-effects regression models with autoregressive correlation structure were used to estimate the association between FeNO and pollutant exposure. Results: The geometric mean of FeNO was 20.9 ppb (geometric standard deviation: 2.2). Mean (SD) personal exposure to PM2.5 was 9.5 (13.4) µg/m3, while for SO2 it was 0.81 (3.21) ppb. Preliminary models indicate that an increase of 10 µg/m3 in previous 8-hour personal exposure to PM2.5 was associated with a 1% (95% CI: 0.1-2.0%) increase in FeNO, adjusted for corticosteroid use, age and sex. Conclusions: Preliminary results indicate an association between personal exposures to PM2.5 and increased airway inflammation in children with asthma.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.256
Teacher spread0.192 · 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