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Record W2055512332 · doi:10.1109/tmech.2014.2356295

Magnetic Characterization of Actuators for an Unmanned Aerial Vehicle

2014· article· en· W2055512332 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2014
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCharacterization (materials science)ActuatorAerospace engineeringComputer scienceAeronauticsRemote sensingEngineeringArtificial intelligenceNanotechnologyMaterials scienceGeology

Abstract

fetched live from OpenAlex

A dipole equivalent modeling approach and experimental results, for relatively small magnetic sources such as servomotors, are presented. Two modeling schemes, viz. the dual permanent magnetic dipole (DuPMaD) and the permanent magnetic dipole (PMaD), are proposed. PMaD assumes only one equivalent magnetic dipole within the physical dimension of the source component, whereas DuPMaD employs a second magnetic dipole with a view to characterize the field more accurately. The equivalent dipole moment vectors and their positions are estimated via fitting experimental data collected on three orthogonal planes around the specimen. Results show good agreements between the model outputs and the experimental data, with both the DuPMaD and the PMaD schemes performing closely in terms of modeling accuracy. Such models may be used to estimate and minimize magnetic interference in various applications such as in geomagnetic surveying using unmanned aerial vehicles considered in this paper.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.505
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.210
Teacher spread0.201 · 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