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Record W2329996253 · doi:10.1061/41002(328)32

Impact of Fastener-Deck Attachment on the Wind Uplift Resistance of Mechanically Attached Roofing Systems

2008· article· en· W2329996253 on OpenAlexaff
Suda Molleti, Steven Kee Ping Ko, Bas A. Baskaran

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsFastenerRoofStructural engineeringDeckMars Exploration ProgramWind engineeringWind tunnelEngineeringGeotechnical engineeringWind speedGeologyAerospace engineeringAstrobiology

Abstract

fetched live from OpenAlex

A roofing system (RS) consists of a waterproof membrane, mechanical attachments, cover board (if present), insulation, and vapor or air barrier (retarder — if present). A roof assembly (RA) is defined as an RS that includes a structural deck. Wind uplift ratings are obtained by subjecting RA mockups to dynamic wind loading. Mechanically Attached Roofing Systems (MARS) are one particular type of roof assemblies in which the membrane is attached to the structural deck using mechanical fasteners. The strength of the fastener-deck interface is an important aspect in the successful design of the wind uplift resistance of mechanically attached roof systems. To quantify the fastener-deck interface influence on the wind uplift performance of MARS, seven different roofing assemblies were constructed and tested under dynamic conditions. The experimental investigation identified three parameters namely deck grade, deck gauge and fastener type that have influence on the wind uplift resistance of MARS. Based on this component characterization, fastener pullout resistance (FPR) is identified as a verification factor for system wind resistance estimation.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.260
Teacher spread0.232 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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