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Sub-cycle time-varying electromagnetic systems

2015· article· en· W1917057327 on OpenAlexaff
Mohamed A. Salem, Christophe Caloz

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsElectromagneticsPermittivityElectromagnetic radiationPhysicsElectromagnetic fieldElectric fieldContext (archaeology)Computational electromagneticsDoppler effectComputational physicsOpticsDielectricEngineering physicsOptoelectronicsQuantum mechanics

Abstract

fetched live from OpenAlex

A sub-cyclic change in the electromagnetic properties of a medium, such as its electric permittivity or magnetic permeability, incurs angular frequency changes in the electromagnetic field propagating through the medium. Such frequency shifts have been mainly studied in context of plasmas, but rarely discussed in electromagnetics textbooks, except for the special case of the Doppler frequency shift, which is essentially a frequency change due to a moving medium (D. K. Kalluri, Electromagnetics of Time Varying Complex Media, 2nd ed. Boca Raton, FL: CRC Press, 2010). Abrupt changing in the medium electromagnetic properties in nonmoving media may thus be used to induce upshifting or downshifting in the angular frequency of the wave. This angular frequency shift is the counterpart of the wave number shift that occurs when the wave propagates through an interface between two half-spaces with different electric properties, as shown in Figure 1.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.197
Teacher spread0.188 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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