MétaCan
Menu
Back to cohort
Record W2626646393

An Integrated methodology to develop moisture management strategies for exterior wall systems

2003· article· en· W2626646393 on OpenAlex
M.K. Kumaran, Phalguni Mukhopadhyaya, S. M. Cornick, Michael Lacasse, M. Z. Rousseau, Wahid Maref, M. Nofal, J. D. Quirt, W. A. Dalgliesh

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNPARC · 2003
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsnot available
Fundersnot available
KeywordsMoistureComputer scienceEnvironmental scienceGeographyMeteorology
DOInot available

Abstract

fetched live from OpenAlex

The MEWS (Moisture Management for Exterior Wall Systems) project produced an integrated methodology for assessing the long-term performance of exterior wall systems with regard to moisture management. The methodology includes the integration of information from a review of field practices, extensive measurements of hygrothermal properties of building materials, definition of environmental loads, investigation on damage functions, large-scale experiments on wind-driven rain penetration and detailed parametric analyses using a benchmarked and advanced hygrothermal model called hygIRC. The paper presents the methodology and the highlights from its applications to assess the performance of several types of wood-frame constructions in North American climatic conditions.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.046
GPT teacher head0.279
Teacher spread0.233 · 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