Literature Analysis on Stachybotrys chartarum and Connections to Sick Building Syndrome
Bibliographic record
Abstract
Sick building syndrome is defined as components of infrastructure that are harmful to human health in various ways ranging from noxious, harmful building materials to toxic fungal contaminants (1). There is mounting emphasis on the need for healthy, sustainably developed buildings as the amount of scientific literature published about sick building syndrome increases. Specifically, there is growing attention regarding the presence of contaminant fungi in buildings and the possible adverse human health effects upon exposure (2). Further, the estimated prevalence of Canadian homes with indoor mold growth is pervasive due to unwanted moisture accumulation in building structures (3). Despite the increasing abundance of scientific research, the existing literature does refer to established knowledge gaps; this includes the need for more primary, quantitative research observing the health effects of indoor mold exposure (3). Black mold (Stachybotrys chartarum) is thought to induce a variety of respiratory, mucosal, and dermatological symptoms in humans (1, 3, 4). These symptoms may arise by direct exposure to spores, indirect exposure or hypersensitivity to fungal antigens, or exposure to mycotoxins which may make inhabitants of contaminated buildings chronically ill (3). Mycotoxins are metabolite products of molds, typically found in mold spores which are the agents of sexual reproduction. The pathogenesis of mold sickness varies from species to species, but all molds found indoors should be treated as a potential hazard risk due to the unknown range of possible consequences after exposure (5). A comprehensive literature review examining the potential health effects of black mold exposure will help to emphasize and articulate the need for employers and homeowners to prioritize building decontamination.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".