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Record W2944853361 · doi:10.4236/wjet.2019.72b002

Analysis of Steel Connections to Resist Progressive Collapse

2019· article· en· W2944853361 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

VenueWorld Journal of Engineering and Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsLakehead University
Fundersnot available
KeywordsConnection (principal bundle)Structural engineeringShear (geology)Progressive collapseContext (archaeology)Displacement (psychology)EngineeringDeformation (meteorology)Computer scienceMaterials scienceGeologyComposite materialReinforced concrete

Abstract

fetched live from OpenAlex

This paper presented a methodology for the analysis and design of steel connections under a double-span connection within the context of preventing progressive collapse. First, various connection models were described and their pros and cons were provided. Then, the load-displacement characteristics of a component-based spring model were described. Thirdly, an experi-mental study on the behaviors of shear tab connections under tension was presented. The main sources of the deformation capacity of the shear tab connections were identified. Finally, a design example of a shear tab connection was provided to illustrate the methodology.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
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 head0.003
GPT teacher head0.206
Teacher spread0.203 · 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