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Record W2090655377 · doi:10.1520/jai11789

A Comparative Evaluation of Three Commercial Instruments for Field Measurements of Reinforcing Steel Corrosion Rates

2005· article· en· W2090655377 on OpenAlexaff
OK Gepraegs, CM Hansson

Bibliographic record

VenueJournal of ASTM International · 2005
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of WaterlooApplied Biological Materials (Canada)
Fundersnot available
KeywordsCorrosionMaterials scienceField (mathematics)MetallurgyForensic engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract In this study, a comparative evaluation was made of three instruments, designed for field monitoring of reinforcing steel corrosion rates. The electrochemical operating principles of each instrument were determined by monitoring the potential and current of each electrode during operation. Corrosion current densities (icorr) of reinforcing steel bar (rebar) in concrete determined with the three different instruments varied by as much as 50 times. The average of the ratios of corrosion rates between any two of the instruments varied between four and 14 times. The size of the polarized area of a section of reinforcing steel is assumed by the configuration of each instrument's counter electrode and guard ring electrode. It was observed that the guard ring electrodes affected the polarization of the reinforcing steel and this effect, together with the different electrode materials, is considered the principal cause of the variations in measured corrosion rate. Corrosion rates of embedded corrosion monitoring probes were also measured. The variation in icorr for measurements on probes was smaller than those on the reinforcing bar and, on average, corrosion rates varied between two and six times. The observation that corrosion monitoring of probes is more consistent than measurements on reinforcing bar suggests that the use of such embedded probes may provide more reliable values for service-life predictions. This consistency was attributed mainly to the known size of the polarized area.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.119
GPT teacher head0.353
Teacher spread0.234 · 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 designBench or experimental
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

Citations19
Published2005
Admission routes1
Has abstractyes

Explore more

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