MétaCan
Menu
Back to cohort
Record W1784147573 · doi:10.1520/stp12557s

Water Absorption in Cold Liquid-Applied Waterproofing

2004· book-chapter· en· W1784147573 on OpenAlexaboutno aff
JC Strong, JR Kovach

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
Fundersnot available
KeywordsWaterproofingAbsorption of waterAbsorption (acoustics)Liquid waterMaterials scienceEnvironmental scienceComposite materialThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Some widely used cold fluid-applied waterproofing materials are prone to failure involving water absorption. These products meet the standards of ASTM Specification for High Solids Content, Cold Liquid-Applied Elastomeric Waterproofing Membrane for Use with Separate Wearing Course (C 836). Experienced investigators of waterproofing systems are familiar with this failure mode; some refer to the convoluted appearance of a membrane after water absorption as “braining.” Our investigation into this mode of failure examines the properties of waterproofing materials and application methods. This report includes the results of testing with four different application methods, and varying conditioning periods. Testing included immersion in water at 50 °C (122 °F). Test specimens absorbed more water than allowed by the Canadian General Standards Board's (CGSB) standard Membrane, Elastomeric, Cold-Applied Liquid, for Non-Exposed Use in Roofing and Waterproofing (CAN/CGSB-37-58).

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: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.010
GPT teacher head0.190
Teacher spread0.180 · 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

Citations1
Published2004
Admission routes1
Has abstractyes

Explore more

Same topicInnovations in Concrete and Construction MaterialsFrench-language works237,207