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Record W2122596388 · doi:10.5539/enrr.v1n1p25

The Effect of Industrial vs. Rural Environment in the Respiratory Status of Schoolchildren

2011· article· en· W2122596388 on OpenAlexvenueno aff
Eleni Papadimitriou, Elena Riza, Leonidas Pililitsis, Georgios Chrousos, Athina Linos

Bibliographic record

VenueEnvironment and Natural Resources Research · 2011
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSpirometryConfoundingAsthmaMedicineIndustrial areaRural areaPediatricsEnvironmental healthPulmonary function testingDemographyInternal medicineGeographyPathologyEnvironmental protection

Abstract

fetched live from OpenAlex

Introduction: This is the first study in Greece where specific methodology is used controlling for all known confounders on the morphology of the children’s spirometric curve in industrial vs. rural area. Materials and Methods: A parental questionnaire and a spirometry test in 62 children in Oinofyta (Industrial area) and 42 in Makrakomi (Rural Area) (5th and 6th Grades, 11-12 years). Results: Higher rates in the industrial area for children’s history of asthma and asthma related symptoms were observed. Subnormal spirometric curve rates in Oinofyta was 25.8% vs. 12.2% in Makarakomi (P=0.074). Similarly, the number of children who had FVC (Forced Vital Capacity) <90% was higher in Oinofyta than in Makrakomi (P=0.037). After adjusting for confounding factors, statistically significant differences in asthma diagnosis and related symptoms, in subnormal spirometric curves and spirometric indices existed between children in the two study groups. Conclusion: Industrial residential area is significantly associated with children’s history of asthma and reduced pulmonary function.

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.071
GPT teacher head0.375
Teacher spread0.304 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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