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Record W2770303658

Experimental Measurement of Magnetization of a Rectangular Bar-shaped Permanent Magnet Utilizing MFMIM

2016· article· en· W2770303658 on OpenAlexaff
M. Hasnat Kabir, Hamidreza Mashayekhi, Sajjad Aftabi, Hamidreza Khodajou-Chokami

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMagnetMagnetizationElectromotive forceBar (unit)Magnetic fieldBenchmarkingCounter-electromotive forceIntensity (physics)Materials scienceMagnetic fluxPhysicsMechanicsElectrical engineeringVoltageOpticsEngineering
DOInot available

Abstract

fetched live from OpenAlex

Purpose: In this investigation, after designing an experimental setup, the magnetization parameter of a rectangular bar-shaped permanent magnet has been determined by a Magnetic Field Magnitude and Intensity Meter device. Methods: In order to achieve this purpose, after finding the geometrical center of mass of the magnet, by moving Hall-Effect sensor in 5mm steps, the magnetic flux intensity has been measured by our recently patented device. Results: The accuracy of the experimental values in comparison with the available commercial grade and analytical equations demonstrated have been confirmed. Our device’s results accuracy has also been approved by benchmarking all results. Following that, the magnetization parameter has been extracted using the numerical technique. Conclusion: Results showed very precise benchmarking and proved the use of this device in measuring the magnetic field in MRI devices. This study will be directed to simulate several subjects like calculating the induced electromotive force

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.271
GPT teacher head0.550
Teacher spread0.279 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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Same venueDOAJ (DOAJ: Directory of Open Access Journals)→Same topicAdvanced MRI Techniques and Applications→French-language works237,207→