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Record W2009538734 · doi:10.1063/1.4769837

Microwave reflection imaging using a magnetic tunnel junction based spintronic microwave sensor

2012· article· en· W2009538734 on OpenAlexaff
Lei Fu, Zhong Cao, Simon Hemour, Ke Wu, D. Houssameddine, Wei Lü, Stephen Pistorius, Y. S. Gui, C.‐M. Hu

Bibliographic record

VenueApplied Physics Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsPolytechnique MontréalUniversity of ManitobaWinnipeg Institute for Theoretical Physics
FundersNational Natural Science Foundation of China
KeywordsMicrowaveMicrowave imagingSpintronicsMaterials scienceOptoelectronicsSIGNAL (programming language)Sensitivity (control systems)RectificationTunnel magnetoresistanceOpticsVoltageElectrical engineeringElectronic engineeringPhysicsTelecommunicationsNanotechnologyEngineeringComputer scienceFerromagnetism

Abstract

fetched live from OpenAlex

A far-field microwave imaging technique has been developed using a spintronic sensor based on a magnetic tunnel junction (MTJ). Such a sensor can directly rectify a microwave field into a dc voltage signal using the Seebeck effect. Thanks to the high conversion efficiency of the microwave rectification in MTJs, the microwave power sensitivity of the spintronic sensor is on the order of 1–10 mV/mW. This high sensitivity allows the sensor to directly measure the coherent spatial scattered microwave field distribution, which gives it the ability to non-destructively detect hidden objects down to a few wavelengths in size.

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)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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

Citations19
Published2012
Admission routes1
Has abstractyes

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