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Record W2808880922 · doi:10.5864/d2018-009

Pilot study: Assessment of the presence of mold in indoor swimming pools

2018· article· en· W2808880922 on OpenAlexafffundvenueabout
Milena Agababova, Chun‐Yip Hon

Bibliographic record

VenueEnvironmental Health Review · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsToronto Metropolitan University
FundersBritish Columbia Centre for Disease ControlPublic Health AgencyPublic Health Agency of Canada
KeywordsMoldEnvironmental scienceRelative humidityIndoor airEnvironmental engineeringBiologyMeteorologyGeographyBotany

Abstract

fetched live from OpenAlex

Indoor swimming pools are the ideal environment for mold growth as they are intentionally humid and warm. Although there are no established safe exposure levels for airborne mold spores, their presence has been associated with adverse health effects that may put individuals at risk. The objective of this pilot study was to observe the occurrence of airborne mold within indoor swimming pools (n = 6) in the Greater Toronto Area. Viable air samples were taken using a Surface Air System air sampler and cultured to quantify and identify airborne mold using microscopy. In addition, relative humidity and temperature were measured and facility characteristics were recorded. Overall, the mold counts were relatively low and were consistent with the literature. However, a biodiverse fungal profile was found at most sites—some of which included fungal groups linked to harmful health effects in humans. Since this was a pilot study, further research is suggested to determine whether the concentration of mold is a cause for concern.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.337
Teacher spread0.301 · 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 designObservational
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

Citations2
Published2018
Admission routes4
Has abstractyes

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