MétaCan
Menu
Back to cohort
Record W2945865193 · doi:10.1615/ihtc12.720

Laboratory Measurements and Benchmarking of an Advanced Hygrothermal Model

2002· article· en· W2945865193 on OpenAlex
Wahid Maref, Kumar Kumaran, Michael Lacasse, M. C. Swinton, David van Reenen

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

VenueProceeding of International Heat Transfer Conference 12 · 2002
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBenchmarkingComputer scienceBusiness

Abstract

fetched live from OpenAlex

Recent research in the field of assessment of hygrothermal response has focused on either laboratory experimentation or hygrothermal modelling, but less work has been reported in which both aspects are combined. Such type of studies can potentially offer useful information regarding the benchmarking of models and related methods to assess hygrothermal performance of wall assemblies. This paper briefly presents an advanced hygrothermal computer model called hygIRC. The paper also reports the results of a series of experiments in which the drying rates of oriented strand board alone or in combination with several sheathing membranes were systematically measured. Results from these experiments are compared with those derived from hygIRC simulations and subsequently used to help benchmark the model. Preliminary results on the shape of the drying curves and the time taken to establish equilibrium moisture content show good agreement between the experiments and simulation. This was one of several steps undertaken in a broader benchmarking exercise to validate the model and its implementation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.617

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 communication0.0000.001
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 head0.050
GPT teacher head0.234
Teacher spread0.184 · 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