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Record W2954918133

Endotoxins in indoor air and settled dust in primary schools in a subtropical climate

2013· article· en· W2954918133 on OpenAlexaff
Heidi Salonen, Caroline Duchaine, Valérie Létourneau, Mandana Mazaheri, Samuel Clifford, Lídia Morawska

Bibliographic record

VenueQUT ePrints (Queensland University of Technology) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité Laval
Fundersnot available
KeywordsEnvironmental scienceHumidityIndoor air qualityRelative humiditySubtropicsAtmospheric sciencesIndoor airAir quality indexAir temperaturePercentileEnvironmental engineeringMeteorologyGeographyEcologyStatistics
DOInot available

Abstract

fetched live from OpenAlex

Endotoxins can significantly affect the air quality in school environments. However, there is currently no reliable method for the measurement of endotoxins and there is a lack of reference values for endotoxin concentrations to aid in the interpretation of measurement results in school settings. We benchmarked the “baseline” range of endotoxin concentration in indoor air, together with endotoxin load in floor dust, and evaluated the correlation between endotoxin levels in indoor air and settled dust, as well as the effects of temperature and humidity on these levels in subtropical school settings. Bayesian hierarchical modeling indicated that the concentration in indoor air and the load in floor dust were generally (<95th percentile) < 13 EU/m3 and < 24,570 EU/m2, respectively. Exceeding these levels would indicate abnormal sources of endotoxins in the school environment, and the need for further investigation. Metaregression indicated no relationship between endotoxin concentration and load, which points to the necessity for measuring endotoxin levels in both the air and settled dust. Temperature increases were associated with lower concentrations in indoor air and higher loads in floor dust. Higher levels of humidity may be associated with lower airborne endotoxin concentrations.

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 score0.010
Threshold uncertainty score0.578

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 science0.0000.001
Research integrity0.0000.000
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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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