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Record W2318325963 · doi:10.1061/9780784479711.059

Can a Single Flood Event Result in Fungal Growth beneath Tile?

2015· article· en· W2318325963 on OpenAlexaff
Kathryn M. Rubin, Erik P. Moore, Ralph E. Moon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSlime Mold and Myxomycetes Research
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsTileImpervious surfaceCeramic tilesEnvironmental scienceFlood mythIntrusionGypsumSubstrate (aquarium)MoldWaste managementEngineeringGeologyMaterials scienceComposite materialGeographyEcologyArchaeology

Abstract

fetched live from OpenAlex

Catastrophic water intrusion events, such as storm-related flooding, require the removal of building materials (i.e., base trim, gypsum board, wood flooring) to prevent or inhibit fungal growth. One material that often prompts inquiry is relatively impervious flooring, specifically, ceramic or porcelain tile and the question, “Are conditions favorable to support fungal growth beneath the tile surface following a moisture exposure event?” A variety of tile installation substrates, such as wood subfloor, gypsum board, and concrete were examined. Our investigation also examined tiles installed in areas of food handling and frequent cleaning that increased likelihood of organic material exposure from sources other than flood conditions. This paper explores the potential for fungal growth underneath tile under a variety of conditions following a flood event. The results suggest that the presence of mold spores beneath a tiled floor may be more closely related to the previous use of the tiled area (food handling, frequent cleaning) and the underlying substrate (plywood or concrete) rather than whether it was flooded.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.366

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)0.0000.000

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 head0.032
GPT teacher head0.239
Teacher spread0.207 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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