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Record W1990466846 · doi:10.5604/12321966.1120595

Quantification of <i>C. globosum</i> spores in house dust samples

2014· article· en· W1990466846 on OpenAlexafffund
Chunhua Shi, Natacha Provost, Tamara Desroches, David Miller

Bibliographic record

VenueAnnals of Agricultural and Environmental Medicine · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMillerSporeMoldEnvironmental scienceArtBiologyBotanyEcology

Abstract

fetched live from OpenAlex

Chaetomium globosum is one of the most common fungi that grows in damp buildings and occurs in agricultural and forestry workplaces. Using sera from atopic patients, we characterized and purified an extracellular chitosanase (Chg47) from C. globosum that is antigenic to humans. The study reports the production of monoclonal antibodies to the protein. Three capture ELISAs were developed for Chg47 for detection of spores and spore and mycelial fragments in dust samples using different mono- and polyclonal antibody combinations. One method is based on an enhanced biotinylated polyclonal antibody as the secondary antibody and coating anti-IgM to capture one of two clones of IgM monoclonal antibodies as the capture antibody. The other method makes use of an enhanced rabbit polyclonal antibody as both the primary and capture antibody. The detection limit of the double PAb method for the Chg47 antigen was 7.6 pg/ml. When the anti-IgM+10B3 clone was used, the detection limit was 61 pg/ml and for anti-IgM+5F12, 122 pg/ml. The detection limit of double PAb method is comparable to methods for the allergen and spores of Aspergillus versicolor in house dust and is more sensitive than other immunoassays for allergens in house including for Stachybotrys chartarum, Aspergillus fumigatus and Alternaria alternata. All three methods had limited cross-reactivity to fungi common in house dust representing a diverse array of taxa.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.237
Teacher spread0.211 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations3
Published2014
Admission routes2
Has abstractyes

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