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Record W3157925543 · doi:10.1007/s42452-021-04575-8

Occupational exposure of librarians to mold spores and metal particles: a real-time case study

2021· article· en· W3157925543 on OpenAlexaff
Alberto Baldelli, Brett Couch, Benjamin Loosley, Karen H. Bartlett

Bibliographic record

VenueSN Applied Sciences · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSporeParticulatesMoldPercentileEnvironmental scienceEnvironmental engineeringMathematicsMaterials scienceStatisticsComposite materialBiologyBotanyEcology

Abstract

fetched live from OpenAlex

Abstract In a university library, activities typical of librarians, such as unpacking boxes, removing books from the shelves, dusting, packing boxes, cataloguing, conservation and repair, photocopying, setting materials for class, and walking in a main hallway, were found to reduce indoor air quality through the production of airborne mold spores, metal dusts, and particulate matter of different size bins. Analyzing three libraries, the activity of conservation generated 9000 spores/m 3 of mold spores, nearing the exposure limit of 10 4 spores/m 3 reported for Penicillium sp., and silver nanoparticles of about 15 µg/m 3 , that over 8 h would exceed the occupational exposure limit of 0.19 µg/m 3 . For none of the activities, the levels of particulate matter with a diameter lower than 2.5 µm (PM 2.5 ) and 10 µm (PM 10 ) did not exceed the 8-h time weight average limits of exposure. However, by analyzing the 5th percentile of the real-time PM 10 data, values of about 1.5 mg/m 3 , which is concerning for occupational exposure. Measuring real-time exposures of PM could generate an estimation of levels of mold spores and metal dusts in libraries. We demonstrate a high Spearman’s rank correlation (0.70) between the 5th percentile of PM with a diameter lower than 1 µm and different metals. A high linearity ( R 2 = 0.85) is obtained between the total average of PM with a diameter lower than 10 µm and mold spores/m 3 .

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.263
Teacher spread0.241 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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