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Record W2583057988 · doi:10.5539/apr.v9n1p93

Improvements to Secondary Windings of Tesla Transformers

2017· article· en· W2583057988 on OpenAlexvenueno aff
R.M. Craven, I.R. Smith, B.M. Novac

Bibliographic record

VenueApplied Physics Research · 2017
Typearticle
Languageen
FieldEngineering
TopicPulsed Power Technology Applications
Canadian institutionsnot available
Fundersnot available
KeywordsElectromagnetic coilTransformerVoltageExcitationComputer scienceElectrical engineeringElectronic engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Impulse excitation of the tuned primary circuit of a Tesla transformer generates a voltage and current response in the similarly tuned secondary circuit that contains both a fundamental component and a series of multiple higher-order modes. This paper investigates the most significant of these modes, in order to demonstrate a design approach that, when applied to the secondary winding, can bring about a reduction in the higher-order modes without significantly affecting the fundamental term. The resulting process leads to an improved spectral purity of the transformer output, making it better suited than existing conventional designs for application in electronic warfare and other high-power systems.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.039
GPT teacher head0.349
Teacher spread0.310 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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