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Record W1971851471 · doi:10.1109/jsen.2012.2216521

Characterization of an Optimized Off-Diagonal GMI-Based Magnetometer

2012· article· en· W1971851471 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 Sensors Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMagnetometerNoise (video)AcousticsElectromagnetic coilMaterials scienceNoise measurementElectrical impedanceWhite noiseMagnetic fieldNuclear magnetic resonanceElectronic engineeringPhysicsNoise reductionEngineeringElectrical engineeringComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

An optimized giant magneto-impedance effect magnetometer has been developed, based on an overall analysis of the measurement chain, including physical material properties, associated detection coil parameters, and equivalent magnetic noise performances. The field response model for the sensing element and the noise model yield good agreement with experimental results. The noise performance of the magnetometer, approximately 1.7 pT/√{Hz} in the white noise region, with a band-pass of about 70 kHz, is competitive with that of other technologies. Present limitations are clearly established, leaving room for further improvements.

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 categoriesInsufficient payload (model declined to judge)
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 score0.079
Threshold uncertainty score1.000

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)0.0010.000

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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