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Record W1673993338

A low-perturbation near-field imager equipped with optical MST probes

2009· article· en· W1673993338 on OpenAlexaff
Hamidreza Memarzadeh Tehran, Jean‐Jacques Laurin, Raman Kashyap

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2009
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPhotodiodeOpticsDiodeLaserNear and far fieldRadio frequencyMicrowaveOptoelectronicsScatteringOptical fiberOptical powerMaterials sciencePhysicsElectrical engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

In this paper, the design and implementation of a near-field microwave imager based on a probe consisting of an optically modulated scatterer (OMS) is described and discussed. The probe uses a commercial-off-the-shelf (COTS) photodiode chip and a short dipole and it fulfils the requirements for a minimum scattering antenna. Measurement using this OMS probe is nearly perturbation-free due to the low scattering of the measured radio-frequency electric field by the optical fiber used to carry the modulating light signal. An array of OMS probes is then developed to eliminate or reduce the delays associated with a mechanical positioning system in a planar near-field setup. Optical power switching between the array elements is done with a switched laser diode array using a number of fiber-pigtailed laser diodes. The performance assessment of the near-field imager, including its linearity and accuracy, is made by comparisons with a known field distribution.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2009
Admission routes1
Has abstractyes

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