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Record W2082480414 · doi:10.1080/1369378031000137350

<i>Stachybotrys chartarum</i>: cause of human disease or media darling?

2003· review· en· W2082480414 on OpenAlexaff
J. David Miller, Thomas Rand, Bruce B. Jarvis

Bibliographic record

VenueMedical Mycology · 2003
Typereview
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsSaint Mary's UniversityCarleton UniversitySt. Mary's UniversityNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsFungusDiseaseBiologyAsthmaMicrobiologyHuman diseaseMedicineImmunologyPathologyBotany

Abstract

fetched live from OpenAlex

This is a review of the literature of associations of the saprotrophic fungus Stachybotrys chartarum sensu lato with human and animal illnesses. This fungus grows on very wet cellulose-based building materials. S. chartarum has been the subject of considerable media attention because of temporal associations of exposure with unexpected and dramatic outcomes such as infant pulmonary hemosiderosis and neurocognitive damage. It is generally accepted that living or working in mouldy environments is associated with building related asthma, exacerbating asthma in mould-sensitive asthmatics and increased rates of upper respiratory disease. However, such relationships are with building-associated moulds, comprising many species that colonize wet or damp building materials, and are not specific to S. chartarum. There is limited evidence that severe lung damage can occur from building exposure to S. chartarum but possibly only under conditions of exposure that approach those associated with handling contaminated straw. There is no positive evidence in the literature to account for putative neurological damage resulting from exposure to this mould.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.055
GPT teacher head0.347
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations85
Published2003
Admission routes1
Has abstractyes

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