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Record W4362690101 · doi:10.1109/jmw.2023.3261901

Near-Field Microwave Microscopy for 3D Surface Assessment of Manufactured Structures

2023· article· en· W4362690101 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

VenueIEEE Journal of Microwaves · 2023
Typearticle
Languageen
FieldEngineering
TopicNear-Field Optical Microscopy
Canadian institutionsMiller Group (Canada)
Fundersnot available
KeywordsMetrologyMicrowaveCoaxialCapacitanceDielectricMaterials scienceSurface metrologyField (mathematics)MicroscopySystem of measurementOptoelectronicsOpticsElectrical engineeringComputer scienceEngineeringPhysicsElectrodeTelecommunicationsComposite materialProfilometerSurface finish

Abstract

fetched live from OpenAlex

Using near-field scanning microwave microscopy as a contact and non-contacting investigative tool for 3D surface metrology with three differing measurement modes, it has been possible to analyse structures that may be difficult for existing metrology systems. The system utilizes the small change in capacitance between a coaxial resonant probe (at around 2 GHz) ending in an open circuit tip, and the sample surface. This is measured in the frequency domain by the shift in the resonance frequency of the voltage transmission coefficient |S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">21</sub> |. It is also possible to investigate various materials (metallics, plastics etc.) owing to their differing dielectric properties. The probe has been tested on a computer-controlled 3D stage but is suitable for incorporation into a commercial co-ordinate measurement machine (CMM) to enhance its capability to inspect the inside surfaces of structures, e.g., threads in small bores.

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 categoriesMeta-epidemiology (narrow)
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 score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.013
GPT teacher head0.300
Teacher spread0.287 · 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