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Record W2301203043 · doi:10.1155/2009/954382

Effects of the Indoor Environment on the Fraction of Exhaled Nitric Oxide in School‐Aged Children

2009· article· en· W2301203043 on OpenAlexaffabout
Thomas Kovesi, Robert Dales

Bibliographic record

VenueCanadian Respiratory Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsChildren's Hospital of Eastern OntarioHealth CanadaUniversity of Ottawa
Fundersnot available
KeywordsExhaled nitric oxideMedicineNitric oxideAsthmaAllergyTobacco smokeExhalationSpirometryInternal medicineImmunologyEnvironmental healthAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: The fractional concentration of exhaled nitric oxide (FeNO) appears to be a good marker for airway inflammation in children with asthma. OBJECTIVE: To evaluate the effect of environmental exposures on exhaled nitric oxide in a community sample of children. METHODS: The relationship among exhaled nitric oxide, underlying disease and home environmental exposures was examined using questionnaire data and measurement of exhaled nitric oxide in a cross-sectional study of 1135 children that included healthy children, and children with allergies and/or asthma who were attending grades 4 through 6 in Windsor, Ontario. RESULTS: Among healthy children, there was a positive association between FeNO and occupancy (P<0.02). Compared with forced air and hot water radiant heat, electric baseboard heating was associated with a significant increase of FeNO in healthy children (P=0.007) and children with allergies (P=0.043). FeNO was not associated with environmental tobacco smoke exposure or reported surface mold. The presence of pet dog(s), but not cats, was associated with a significantly lower FeNO in healthy children (P<0.001) and in children with reported allergies (P<0.001). CONCLUSIONS: The type of heating system, but not previously reported environmental tobacco smoke or mold exposure appears to affect exhaled nitric oxide in children. Exposure to different types of pets may have disparate effects on airway inflammation.

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)0.000
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 score0.035
Threshold uncertainty score0.315

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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

Citations22
Published2009
Admission routes2
Has abstractyes

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