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Record W2078108100 · doi:10.5006/1.3277577

Evaluation of Reinforcement Corrosion in Repaired Concrete Bridge Slabs—A Case Study

2003· article· en· W2078108100 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCORROSION · 2003
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaPublic Works and Government Services CanadaGovernment of Canada
KeywordsCorrosionCarbonationConcrete coverSlabChlorideReinforcementMaterials scienceNondestructive testingReinforced concreteHalf-cellStructural engineeringPolarization (electrochemistry)Composite materialGeotechnical engineeringForensic engineeringMetallurgyElectrochemistryEngineeringElectrodeChemistry

Abstract

fetched live from OpenAlex

Results of a study of reinforcement corrosion in four repaired concrete slab sections taken from an old bridge are presented, as well as results measured on electrochemical cells. Significant evidence is provided to help the inspection engineer to interpret the corrosion survey data taking into account the specifics of the environmental conditions that prevailed during the survey. The measurements comprised half-cell potential, linear polarization, and concrete resistivity, which are known to be sensitive to the ambient environment, especially to oxygen and water in concrete. Some semi-destructive tests, including chloride concentration, chloride permeability, and carbonation depth, were also carried out to assist the analysis and to support the results of the nondestructive corrosion testing techniques. The concrete cover of the slab samples was later removed to assess the actual state of corrosion of the reinforcement and to compare it to the corrosion predicted from the corrosion surveys. This study shows that each corrosion measurement technique has its specific advantages and limitations. Better prediction of corrosion can be obtained by analyzing the data collected from various evaluation methods with careful consideration for the effects of environmental conditions.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.054
GPT teacher head0.293
Teacher spread0.239 · 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