Bibliographic record
Abstract
Bioaerosols include microbial cells (microorganisms), their reproductive units, and associated metabolites that are volatile or small enough to sufficiently achieve aerial dispersion. Categories of bioaerosols include viruses, bacteria, fungi, algae, and protozoa and their products (Burge, 1990a). These microorganisms and their byproducts are naturally occurring and are considered to be ubiquitous. Under certain environmental conditions, many bioaerosols can cause varying symptoms, disorders, and diseases in humans, and they can survive for extended periods. Microorganisms are a normal and essential component of the earth’s terrestrial and aquatic ecosystems. Bacteria and fungi break down the complex molecules found in dead organic materials from animals and plants, and recycle minerals and carbon to simple substances such as carbon dioxide and nitrates. Microorganisms such as saprophytic bacteria and fungi, which derive nutrients from non-living materials in the environment, are commonly found in the soil and the atmosphere (Morey and Feeley, 1990). Many of the medical symptoms of bioaerosol exposure are accentuated in indoor environments due to the accumulation of the specific bioaerosol(s) as the result of poor building ventilation. Microbial contamination in buildings can usually be tracked back to either unsanitary mechanical equipment (e.g., growth in condensate pans, dirty filters and/or ductwork) or excess moisture (e.g. flooding, leaks, condensation, damp filters, or elevated humidity) (Burge, 1987; Morey et al., 1986). Excessive mold and/or bacterial concentrations in indoor air primarily impact the health of allergy-prone (atopic) individuals. Such persons may experience the relatively common symptoms of allergic rhinitis or asthma shortly after initial exposure (Canadian Public Health Association, 1987). Much less frequently, airborne microorganisms cause
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.016 |
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".