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Record W2105467825 · doi:10.5194/gi-2-213-2013

A radiation hardened digital fluxgate magnetometer for space applications

2013· article· en· W2105467825 on OpenAlexaffabout
David M. Miles, J. R. Bennest, I. R. Mann, D. K. Millling

Bibliographic record

VenueGeoscientific instrumentation, methods and data systems · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMagnetometerFluxgate compassVan Allen radiation beltMagnetic fieldSpace environmentPhysicsCompensation (psychology)Electrical engineeringNoise (video)Computer scienceMagnetosphereEngineeringGeophysics

Abstract

fetched live from OpenAlex

Abstract. Space-based measurements of Earth's magnetic field are required to understand the plasma processes responsible for energising particles in the Van Allen radiation belts and influencing space weather. This paper describes a prototype fluxgate magnetometer instrument developed for the proposed Canadian Space Agency's (CSA) Outer Radiation Belt Injection, Transport, Acceleration and Loss Satellite (ORBITALS) mission and which has applications in other space and suborbital applications. The magnetometer is designed to survive and operate in the harsh environment of Earth's radiation belts and measure low-frequency magnetic waves, the magnetic signatures of current systems, and the static background magnetic field. The new instrument offers improved science data compared to its predecessors through two key design changes: direct digitisation of the sensor and digital feedback from two cascaded pulse-width modulators combined with analog temperature compensation. These provide an increase in measurement bandwidth up to 450 Hz with the potential to extend to at least 1500 Hz. The instrument can resolve 8 pT on a 65 000 nT field with a magnetic noise of less than 10 pT/√Hz at 1 Hz. This performance is comparable with other recent digital fluxgates for space applications, most of which use some form of sigma-delta (ΣΔ) modulation for feedback and omit analog temperature compensation. The prototype instrument was successfully tested and calibrated at the Natural Resources Canada Geomagnetics Laboratory.

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)0.001
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.319
Teacher spread0.301 · 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

Citations25
Published2013
Admission routes2
Has abstractyes

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