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Record W2002816552 · doi:10.1177/109719630002400103

Freezing-Thawing Processes in Glass Fiber Board

2000· article· en· W2002816552 on OpenAlexafffund
Shuichi Hokoi, Masanori Hatano, Mamoru Matsumoto, M.K. Kumaran

Bibliographic record

VenueJournal of Thermal Envelope and Building Science · 2000
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsNational Research Council Canada
FundersNational Research Council Canada
KeywordsMaterials scienceMoistureCondensationGlass fiberComposite materialFiberPhase (matter)Water contentHeat transferPorosityWater vaporThermodynamicsGeotechnical engineeringMeteorologyGeologyChemistry

Abstract

fetched live from OpenAlex

For the prevention of vapor condensation and accompanying damage in cold regions, the behavior of water and ice in porous materials should be understood. In this study, experiments on the freezing-thawing processes in a glass fiber board, which is a typical insu lation, were conducted. The freezing-thawing processes were analyzed with the use of si multaneous heat and moisture transfer equations that accounted for the existence of ice. The result of the analysis agrees well with that of the experiment. In materials with large pores such as glass fiber board, the moisture transfers mainly in the gaseous phase. As a re sult, the maximum ice content is found at the colder boundary of the wall, which differs from the result in our previous investigation [1] for Leda Clay with pores that are much smaller.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.012
GPT teacher head0.227
Teacher spread0.214 · 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 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
Published2000
Admission routes2
Has abstractyes

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Same venueJournal of Thermal Envelope and Building ScienceSame topicHygrothermal properties of building materialsFrench-language works237,207