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DETERMINAÇÃO DO DESEMPENHO DE UM MIT A PARTIR DOS ENSAIOS A VAZIO E ROTOR BLOQUEADO

2022· article· pt· W4323020773 on OpenAlexaff
Daniel Kingo Kihara, Renato Silva Alves

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsFord Motor Company (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesComputer scienceArt

Abstract

fetched live from OpenAlex

Este artigo demonstrou os ensaios a vazio, rotor bloqueado e de corrente contínua realizados em um motor elétrico de indução trifásico (MIT) a fim de adquirir os dados para aplicação nas equações que definem suas características de desempenho, uma vez que não são conhecidas. As variáveis que compõem o equacionamento foram obtidas através do circuito elétrico equivalente monofásico que representa o MIT em regime permanente e este foi demostrado e aplicado em um código no programa GNU Octave. Os resultados obtidos do código foram comparados aos dados de catálogo do fabricante e garantiu sua veracidade.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.033
GPT teacher head0.270
Teacher spread0.237 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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