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Record W3163239157 · doi:10.1109/mim.2021.9436100

Measurement of Voltage, Current and Power at Distorted Waveforms

2021· article· en· W3163239157 on OpenAlexaff
Branislav Djokić, Harold Parks

Bibliographic record

VenueIEEE Instrumentation & Measurement Magazine · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Electrical Measurement Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsVoltageElectrical engineeringCurrent (fluid)WaveformPower (physics)Electric power systemElectric powerTotal harmonic distortionAlternating currentVoltage optimisationEngineeringPhysicsAC power

Abstract

fetched live from OpenAlex

Electric power systems have been designed to operate under sinusoidal voltage and current conditions at power frequencies, mainly 50 Hz and 60 Hz, and by far most electrical energy transmission occurs at 50 Hz and 60 Hz. Electric utilities are responsible for providing a sinusoidal voltage to their residential, commercial and industrial customers. The customers are, on their side, responsible for not causing excessive distortion of the voltage and current in the system. Since voltage and current, in practice, are periodical but not exactly sinusoidal, they contain higher frequency components—harmonies—in addition to the fundamental frequency component (50 Hz or 60 Hz).

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.250
Teacher spread0.223 · 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
GenreMethods

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

Citations2
Published2021
Admission routes1
Has abstractyes

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