MétaCan
Menu
Back to cohort
Record W2086596322 · doi:10.1109/tie.2012.2183839

A Novel Single-Stage Multilevel Type Full-Bridge Converter

2012· article· en· W2086596322 on OpenAlexaff
Mehdi Narimani, Gerry Moschopoulos

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsWestern University
Fundersnot available
KeywordsRectifier (neural networks)Single phaseSingle stageComputer scienceHalf bridgeConvertersElectronic engineeringControl theory (sociology)CapacitorTopology (electrical circuits)EngineeringVoltageControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

A new three-phase single-stage rectifier is proposed in this paper. The outstanding features of the proposed rectifier are that it can produce input currents that do not have deadband regions and an output current that can be continuous when the converter is operating from maximum load to at least half of the load. In this paper, the operation of the new converter is explained, its features and design are discussed in results, and its operation is confirmed with experimental results obtained from a prototype.

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: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.065
GPT teacher head0.254
Teacher spread0.190 · 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

Citations50
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Industrial ElectronicsSame topicAdvanced DC-DC ConvertersFrench-language works237,207