Microbiology on <b> <i>Indoor Air `99</i> </b>- What is New and Interesting? An Overview of Selected Papers Presented in Edinburgh, August, 1999
Bibliographic record
Abstract
A multidisciplinary approach to microbiological implications of indoor air is fruitful for research as well as management of health and building problems. The Finnish and the Danish mold programs are examples of such productive collaborative studies. Dust samples taken from classrooms in schools where occupants complain of building-related symptoms (BRS) demonstrated an inflammatory potential in vitro, measured as a release of cytokine interleukin (IL)-8. An increase of the metabolite NO and liberation of tumor necrosis factor (TNF)-alpha and other cytokines during exposure were obtained in vivo, was presented based on these programs and on epidemiological studies on residential fungal contamination and health conducted in Canada and The Netherlands. New methods for assessing fungal exposure are PCA analysis for the toxigenic mold Stachybotrys chartarum and EPS-Asp/Pen for detecting of Aspergillus and Penicillium in dust. Based on a limited data set it is shown that emission rates of fungal spores are inversely proportional to relative humidity (RH), directly related to flow rate and to surface loading. Poor maintenance, risk constructions and risk materials are described in several studies as the main causes of water damage in buildings.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.011 |
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".