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Record W4289773909 · doi:10.1520/stp1604-eb

Durability of Building and Construction Sealants and Adhesives: 6th Volume

2018· book· en· W4289773909 on OpenAlexaboutno aff
Christopher C. White, Hiroyuki Miyauchi

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicStructural Analysis of Composite Materials
Canadian institutionsnot available
Fundersnot available
KeywordsDurabilityVolume (thermodynamics)Composite materialMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Description Get 17 peer-reviewed papers in the sixth edition of this valuable book for the building industry. Understanding sealant durability, and how long a sealant will perform, is critical to the built environment. ASTM building sealant standards are used globally in the development of commercial and multi-use buildings. International authors from Germany, Japan, Hong Kong, and the United States present state-of-the-art research on the durability of structural and weatherproofing sealants and adhesives. Topics include Sponsored by ASTM Committee C24 on Building Seals and Sealants, this publication features papers that were presented at the Sixth Symposium on the Durability of Building and Construction Sealants and Adhesives held in Toronto, Ontario, Canada, in June 2017.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.124
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1240.086

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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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