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Record W4387102302 · doi:10.3390/engproc2023043042

Test of Slip-Critical Connection System with Embedded Nuts for Aluminum Bridge Application

2023· article· en· W4387102302 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Structural Analysis Methods
Canadian institutionsWSP (Canada)Centre Québécois de Recherche et de Développement de l'Aluminium
Fundersnot available
KeywordsAluminiumSlip (aerodynamics)TorqueStructural engineeringNutBridge (graph theory)FabricationBridge deckMaterials scienceComputer scienceDeckEngineeringMechanical engineeringComposite material

Abstract

fetched live from OpenAlex

Aluminum is a common material in construction and relatively new in infrastructure, such as bridges. One advantage of aluminum is the production of complex geometry extrusions, which optimizes the mass of components. In order to assemble aluminum deck panels, a mechanical assembly method must be used. One solution is to access the fasteners (nuts) in closed areas of the extrusions. As was found, to embed the nuts in an aluminum flat bar, the goal was to assure non-slip grip at maximum torque and minimum fabrication cost. Full-scale physical tests were performed to verify the compliance with standardized turn-of-nut tightening requirements. The good test results will help introduce this solution in future aluminum bridge construction projects and improve bridge standards.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.840
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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