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Record W1518178314 · doi:10.1109/tdc.2001.971214

New simulation tools for power systems

2002· article· en· W1518178314 on OpenAlexaff
P.G. McLaren, Paul Forsyth, A. Perks, Peter Bishop

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsRTDS Technologies (Canada)
Fundersnot available
KeywordsComputer scienceWaveformFeature (linguistics)Power (physics)Mode (computer interface)SimulationHuman–computer interactionTelecommunications

Abstract

fetched live from OpenAlex

A brief history of analog simulators is given leading up to the development of the new types of digital simulator. Examples of the older analog simulators is followed by examples of their digital counterparts. Typical output waveforms from the new simulators are shown both in playback and interactive mode. Specific examples are given of the increase in testing efficiency using the new real time digital simulators with a batch testing feature.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.024
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0240.010

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 head0.030
GPT teacher head0.229
Teacher spread0.200 · 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 designSimulation or modeling
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

Citations10
Published2002
Admission routes1
Has abstractyes

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