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Record W4244305625 · doi:10.1520/stp48951s

Assessing the Effectiveness of Wall-Window Interface Details to Manage Rainwater—Selected Results from Window Installation to a Wall Sheathed in Extruded Polystyrene

2010· book-chapter· en· W4244305625 on OpenAlexaff
M. A. Lacasse, M. Armstrong, G. Ganapathy, M. Rousseau, S. M. Cornick, D. Bibee, D. Shuler, A. Hoffee

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsWindow (computing)Rainwater harvestingExpanded polystyreneInterface (matter)Materials sciencePolystyreneComposite materialComputer scienceWorld Wide WebPolymer

Abstract

fetched live from OpenAlex

The detailing of wall-window interfaces and the consequences of defective installation of windows are an on-going concern in North America. This paper concerns laboratory evaluation of the water leakage performance of a select set of window-wall interface details. The details were for windows with mounting flanges installed in wood-frame walls sheathed with rigid extruded polystyrene foam. The tests were performed on a single full-scale test assembly in which two identical windows were installed by two similar but nonetheless different means. Each detail included a sill pan intended to collect water that gained entry into the assembly and thus was designed to be robust (tolerant of flaws). Tests were performed over a series of different water loading (spray) rates and over a series of different air pressure differentials at each spray rate. Air leakage rates through the window opening were monitored; they were controlled by a unique methodology. Leakage paths were introduced in the window frames, and these paths were alternatively blocked or opened to permit evaluation of the performance of the installation details under two different assumed conditions of window leakage. Air pressure distribution within the assemblies was monitored during spray testing. The wall assembly was designed to permit observation of water entry in it and to allow measurement of water entry to, or drainage from, various locations within the assembly. Results on water entry and management for the two wall-window interface configurations are given, and effectiveness of the details is discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.250
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations1
Published2010
Admission routes1
Has abstractyes

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