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Record W2020880276 · doi:10.1139/l06-082

Load and resistance data for precast stringer highway bridges

2006· article· en· W2020880276 on OpenAlexfundvenueaboutno aff
Daman K. Panesar, F. Michael Bartlett

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPrecast concreteStructural engineeringStringerEngineeringAxleDeckAxle loadDeflection (physics)Ultimate tensile strengthBending momentGeotechnical engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Statistical parameters for the load effects and resistances of precast "type G" stringer bridges erected in Alberta since the late 1950s are presented to assist practicing engineers assessing similar bridges using the mean load method. The load effect data include unit weight data for normal weight and two lightweight concretes; traffic volumes, gross vehicle weights, and single, tandem, and tridem axle weights observed on primary, secondary, and local roads; and dynamic load allowances for shear and bending moment on short span bridges. Extreme annual traffic loads are derived. The resistance data include compressive and tensile strengths of normal weight and two lightweight concretes and yield strengths for corroded and uncorroded reinforcing steel. Additional statistical parameters are presented to account for other readily discerned bridge-specific idealization factors that affect the reliability indices. Professional factors for flexural and shear resistance are derived using experimental data reported from past investigations of type G stringers by others.Key words: concrete, core tests, corrosion, dynamic load allowance, material properties, single axles, tandem axles, tridem axles, reliability.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.823

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 head0.014
GPT teacher head0.192
Teacher spread0.178 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2006
Admission routes3
Has abstractyes

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