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Biodeterioration Models for Building Materials: Critical Review

2019· article· en· W2980094374 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Architectural Engineering · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsD-Wave Systems (Canada)University of Victoria
Fundersnot available
KeywordsArchitectural engineeringEnclosureSustainabilityBuilding designEngineeringBuilding scienceBuilt environmentConstruction engineeringField (mathematics)Civil engineeringEcology

Abstract

fetched live from OpenAlex

Biodeterioration of building materials due to poor hygrothermal conditions is a major concern for the sustainability of buildings and the health and safety of occupants. The risks of biodeterioration are accentuated in high-efficiency buildings, requiring further design considerations. Researchers across the world have tried to characterize this issue through a combination of field experience, modeling, and controlled laboratory investigations. However, integration of these research outputs in building enclosure design analysis is an unfinished agenda, partly due to the lack of coordination between engineering researchers, building enclosure designers, and biologists. This paper critically reviews the research to date on biodeterioration models of building materials (e.g., wood) from the perspective of a building scientist and identifies the needs for further research initiatives that will facilitate the integration of biodeterioration models in building enclosure design analysis through national and international building code regulations and standards.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.244

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 head0.020
GPT teacher head0.233
Teacher spread0.212 · 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