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Record W2334438847 · doi:10.1061/41016(314)120

Evaluation of Temperature Data of Confederation Bridge: Thermal Loading and Movement at Expansion Joint

2008· article· en· W2334438847 on OpenAlexaffabout
Dongning Li, Marc A. Maes, Walter H. Dilger

Bibliographic record

VenueStructures Congress 2008 · 2008
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsCanadian Society of Petroleum GeologistsTrusted Positioning (Canada)University of Calgary
Fundersnot available
KeywordsTemperature gradientJoint (building)Displacement (psychology)Bridge (graph theory)GeologyThermalSection (typography)Structural engineeringTemperature measurementVertical displacementBox girderMaximum temperatureMaterials scienceThermal expansionGirderEngineeringComposite materialComputer sciencePhysicsMeteorology

Abstract

fetched live from OpenAlex

Examination of the critical observed temperature profiles will lead to the following conclusions: 1 Thick bottom slabs in deep sections (Sections 1 and 2) lead to lower than predicted temperatures and significant tensile stresses in these slabs. 2 The difference in temperature between the two webs of box girders are the source of a horizontal thermal gradient in deep box girder sections (Sections 1 and 2). For shallower section (Section 3), this was not observed. 3 The effect of horizontal temperature gradient cannot be ignored for deep sections when calculating continuity stresses. For shallow section this can be ignored. 4 The maximum seasonal displacement the bridge experienced during the 3-year period was found to be 226 mm. The Canadian standard CSA-S6-00 gives a good estimate for maximum temperature but seriously underestimates minimum temperature and differential temperature, for deep sections. Also, the code lacks guidance regarding design values for horizontal differential temperature.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.069
GPT teacher head0.279
Teacher spread0.210 · 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 designObservational
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

Citations4
Published2008
Admission routes2
Has abstractyes

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