Bibliographic record
Abstract
PURPOSE OF REVIEW: Over the past 40 years, the circumstances where fungal bioaerosols are major issues have shifted because of changes in the industrial sector from mainly agriculture to operations, including composting, cannabis production and forestry in hot humid conditions. Changes in the design and operation of nonindustrial workplaces meant that mould and dampness became major issues that are just being reduced. This review attempts to frame that history offers a perspective on the current thinking on mechanisms and provide potentially useful sources of information for physicians and their patients. RECENT FINDINGS: The major impact of fungal exposures is not only from their allergens but also from an array of Danger-Associated Molecular Pattern molecules, possibly the most important of which is the type of glucan found in moulds that grow in damp buildings, wood chips and crops, that is beta 1, 3 D glucan in triple helical form. Located in lung epithelia, the dectin receptor is exquisitely sensitive to this compound. Except in some agricultural workplaces, low molecular weight secondary metabolites often mischaracterized as mycotoxins play little, if any, role on population health. SUMMARY: There has been a convergence in thinking between the allergy and industrial hygiene communities as well as government agencies on mould and occupational health. This has led to some useful strategies for better managing these issues as well as increasing consumer awareness.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".