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Microbial volatile organic compounds in the air of moldy and mold-free indoor environments

2008· article· en· W2146703464 on OpenAlexaff
Hans Schleibinger, Detlef Laußmann, Carl‐Gustaf Bornehag, D. Eis, Henning Rueden

Bibliographic record

VenueIndoor Air · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMoldEnvironmental scienceIndoor airEnvironmental chemistrySick building syndromeWaste managementIndoor air qualityEnvironmental engineeringChemistryBiologyEngineering

Abstract

fetched live from OpenAlex

UNLABELLED: A single-blinded study was performed to analyze whether indoor environments with and without mold infestation differ significantly in microbial volatile organic compounds (MVOC) concentrations. Air sampling for MVOC was performed in 40 dwellings with evident mold damage and in 44 dwellings, where mold damage was excluded after a thorough investigation. The characteristics of the dwellings, climatic parameters, airborne particles and air exchange rates (AER) were recorded. The parameters mold status, characteristics of the interiors and measured climatic parameters were included in the multiple regression model. The results show no significant association between most of the analyzed MVOC and the mold status. Only the compounds 2-methyl-1-butanol and 1-octen-3-ol indicated a statistically significant, but weak association with the mold status. However, the concentrations of the so-called MVOC were mainly influenced by other indoor factors. 2-Methylfuran and 3-methylfuran, often used as main indicators for mold damage, had a highly significant correlation with the smoking status. These compounds were also significantly correlated with the humidity and the AER. The compounds 3-methyl-1-butanol, 2-hexanone, 3-heptanone and dimethyl disulfide were weakly correlated with the recorded parameters, the humidity being the strongest influencing factor. Only 2-methyl-1-butanol and 1-octen-3-ol showed a statistically significant association with the mold status; however, only a small portion (10% in this case) of the total variability could be explained by the predictor mold status; they do not qualify as indicator compounds, because such minor correlations lead to a too excessive part of incorrect classifications, meaning that the diagnostic sensitivity and specificity of these compounds are too low. PRACTICAL IMPLICATIONS: The assumption that mold infestations might be detected by microbial VOC emissions must be considered with great reservation. The major part of the total variability of the measured MVOC concentrations originates from not known influencing factors and/or from factors not directly associated with the mold status of the dwellings (confounders). More specific and sensitive markers for the assessment of the mold status should be found, if the screening for mold infestations should be performed by volatile organic compounds.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.202
Teacher spread0.191 · 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

Citations103
Published2008
Admission routes1
Has abstractyes

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