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Record W2118324935 · doi:10.1109/i2mtc.2013.6555373

An embedded inductively coupled printed circuit board based corrosion potential sensor

2013· article· en· W2118324935 on OpenAlexaff
Khalada Perveen, Greg E. Bridges, Sharmistha Bhadra, D. J. Thomson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCorrosionElectromagnetic coilPrinted circuit boardVaricapMaterials scienceResonatorCorrosion monitoringElectrical engineeringOptoelectronicsElectronic engineeringCapacitanceEngineeringMetallurgyElectrodePhysics

Abstract

fetched live from OpenAlex

In this work we demonstrate a printed circuit board based wireless inductively coupled corrosion potential sensor for monitoring steel reinforced concrete civil infrastructure. The sensor uses a coupled coil resonator whose resonant frequency varies due to the corrosion potential being applied across a varactor diode. The sensor is interrogated externally by an interrogator coil. An accelerated corrosion test was carried out on embedded sensor. The result shows that it can measure corrosion potentials with a resolution of less than 10 mV. The sensor is simple in design, inexpensive and passive making it battery less option for long-term corrosion monitoring, and widely deployable for civil structure.

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 categoriesInsufficient payload (model declined to judge)
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 score0.924
Threshold uncertainty score0.995

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)0.0060.000

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 head0.013
GPT teacher head0.217
Teacher spread0.204 · 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.

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

Citations5
Published2013
Admission routes1
Has abstractyes

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