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Record W4410292749 · doi:10.1117/12.3053412

Coplanar capacitive sensing for nondestructive evaluation

2025· article· en· W4410292749 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCapacitive sensingNondestructive testingMaterials scienceComputer scienceEngineeringElectrical engineeringMedicineRadiology

Abstract

fetched live from OpenAlex

Amongst various nondestructive evaluation techniques, coplanar capacitive sensing offers key advantages: it is singlesided, non-contact, and capable of investigating both electrically conductive and insulating materials. Although this technique has been a research topic for nearly two decades, its use for nondestructive evaluation applications is still considered an emerging technology. This is due to multiple factors – beyond just the dielectric properties of the test piece – that can affect capacitance. The present work discusses the principles of capacitive sensing and potential probe design selection based on numerical simulations. Numerical models were employed for probe optimization, with a focus on sensitivity to electric permittivity and lift-off. Additionally, applications of the technique in evaluating tile misalignment in ceramic armor arrays, as well as inspecting composite aircraft structures subjected to lightning strikes are presented.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.219

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 head0.038
GPT teacher head0.298
Teacher spread0.260 · 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