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Record W4382132698 · doi:10.14293/icmb230008

Microbial VOC emissions from mould growth on building materials under various relative humidity conditions

2023· article· en· W4382132698 on OpenAlexaffabout
Wenping Yanga, Stephanie So, Apoorv Shah, Gang Nong, Daniel Lefebvre, Maurice Defo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsRelative humidityHumidityVolatile organic compoundEnvironmental scienceEnvironmental chemistryTerpeneChemistryOrganic chemistryMeteorology

Abstract

fetched live from OpenAlex

<p class="first" id="d7977347e90">Microbial volatile organic compounds (MVOC) emissions were investigated on six typical Canadian building materials with and without mould growth under various relative humidity conditions. The impact of relative humidity on material emissions was also evaluated. Specimens were incubated in an incubation chamber under constant environmental conditions, volatile organic compounds (VOC) emissions and in-situ mould growth on building materials were monitored. The identified MVOCs were mostly ketones, terpenes including terpenoids and alcohols, whose evolutions were correlated with mould growth activity. Experimental results also confirmed that high relative humidity could promote mould growth activity and increase VOC/MVOC emissions from the building materials.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.001

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.

Opus teacher head0.032
GPT teacher head0.248
Teacher spread0.216 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2023
Admission routes2
Has abstractyes

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