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Record W2156158219 · doi:10.1002/fam.880

Thermal properties of lightweight‐framed construction components at elevated temperatures

2005· article· en· W2156158219 on OpenAlexafffundabout
Noureddine Bénichou, Mohamed A. Sultan

Bibliographic record

VenueFire and Materials · 2005
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsNational Research Council Canada
FundersFPInnovations
KeywordsThermal conductivityThermal expansionThermalThermal bridgeMaterials scienceThermal massThermal insulationComposite materialThermal transmittanceFire resistanceGypsumStructural engineeringThermal resistanceEngineeringThermodynamics

Abstract

fetched live from OpenAlex

Abstract Fire resistance behaviour of lightweight‐framed assemblies is determined by defining the thermal and structural performances of the assembly when exposed to fire. To adequately model thermal behaviour in a lightweight wood‐framed assembly, thermal properties of the components of the assembly at elevated temperatures must be well defined. This paper presents results of measurements of thermal properties at elevated temperatures of construction materials commonly used to build lightweight wood‐framed assemblies that were conducted at the National Research Council of Canada since 1990. The test results, in graphical form, are given as a function of temperature for thermal conductivity, specific heat, mass loss and thermal expansion/contraction for wood, gypsum and insulation. In addition, the effects of temperature on the thermal conductivity, specific heat, mass loss and thermal expansion/contraction of these materials are discussed. Finally, in addition to providing a resource of information, this paper also identifies the additional thermal property tests required to complete the matrix of information. Copyright © 2005 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.285

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 head0.012
GPT teacher head0.175
Teacher spread0.162 · 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 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

Citations55
Published2005
Admission routes3
Has abstractyes

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