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Record W2989024943 · doi:10.1109/tim.2002.806010

Design and implementation of a calorimetric measurement facility for determining losses in electrical machines

2002· article· en· W2989024943 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Instrumentation and Measurement · 2002
Typearticle
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCalibrationMeasurement uncertaintyInduction motorTemperature measurementEngineeringComputer scienceElectrical engineeringReliability engineeringControl engineeringAutomotive engineeringMechanical engineeringElectronic engineeringVoltageMathematicsPhysics

Abstract

fetched live from OpenAlex

The measurement of the total losses of electrical machines is of most interest to designers for verifying their calculations. We show the limitations of the conventional input-output procedure leading to loss figures. An alternative method is proposed. For this purpose, a calorimetric measurement facility was designed and implemented. This paper is intended to present the calibration procedure for this facility, as well as results of tests performed on a 10 hp (7.5 kW) induction motor.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

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

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 head0.096
GPT teacher head0.286
Teacher spread0.189 · 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