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Record W3195764221 · doi:10.1109/mmm.2021.3086335

Recycling Ambient RF Energy: Far-Field Wireless Power Transfer and Harmonic Backscattering

2021· article· en· W3195764221 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 Microwave Magazine · 2021
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsElectrical engineeringWireless power transferWirelessHertzPower (physics)SPARK (programming language)Energy transferPhysicsEngineeringTransmission (telecommunications)Field (mathematics)HarmonicTelecommunicationsAcousticsComputer scienceEngineering physics

Abstract

fetched live from OpenAlex

It all started with a spark. Let us rewind back to 1887, in Germany. The days were getting cooler in the garden of the Technische Hochschule in Karlsruhe as Heinrich Rudolf Hertz was setting up the first-ever far-field wireless power transmission with increasingly more power [1]. He was striving to demonstrate the wireless nature of electromagnetic waves and propagation. Moreover, as no high-frequency (nearly 100 MHz) voltmeter was available at that time for his experiment, he had to transmit enough power to generate a spark-hundreds of volts!-at the receiver to validate the famous theory of James Clerk Maxwell.

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 score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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