Emission patterns and emission rates of MVOC and the possibility for predicting hidden mold damage?
Bibliographic record
Abstract
UNLABELLED: Laboratory trials were performed in order to search for the variety of the production of microbial volatile organic compounds (MVOC), which could be used as indicators for hidden mold damage. Concerning MVOC production the experiments showed a dependency on the mold genus/species, the different strains used and the building materials used as substrate. It could be proved that the production of certain MVOC is not consistent at all times. On the whole low emission rates in terms of microg/h/m2 of the MVOC were found. Extrapolating the emissions rates from the laboratory trails to an indoor air situation results in concentrations below the analytical detection limit in most cases. According to these results only heavy or very large fungal contaminations might be detected by this method in indoor air. The studies were performed at the Institute of Hygiene and Environmental Medicine, Charite, Germany. PRACTICAL IMPLICATIONS: Microorganisms like bacteria and molds produce a huge variety of substances, and a part of them are released into the environment. Some compounds like, e.g. alcohols or ketones are volatile, therefore found in the air and called MVOC. Those compounds were considered helpful to track especially hidden mold damage. The study presented here showed, that the emission pattern varies from genus to genus and sometimes even from fungal strain to fungal strain. The results concerning the emission rates from different infested building materials proved, that the concentrations produced are much too low to be detected in indoor air, especially considering the dilution because of ventilation. Therefore, we conclude that MVOC should not be used as predictors for mold damage in indoor environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".