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Record W3120818739 · doi:10.1109/tps.2020.3045366

Fixed Bias Probe Measurement of a Satellite Floating Potential

2021· article· en· W3120818739 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 Transactions on Plasma Science · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCompute Canada
KeywordsLangmuir probeSpacecraftSatelliteOrbit (dynamics)Temporal resolutionRange (aeronautics)PhysicsComputational physicsVoltageData setMeasure (data warehouse)Orbital motionGeodesyRemote sensingPlasma diagnosticsComputer sciencePlasmaOpticsMathematicsAerospace engineeringGeologyClassical mechanicsStatistics

Abstract

fetched live from OpenAlex

A simple sensor is described to measure satellite potentials. The proposed instrument consists of two small spherical Langmuir probes biased to different fixed voltages, from which currents are measured. A predictive model is constructed for spacecraft floating potentials by combining the orbital motion limited (OML) approximation for spherical probes, and a multivariate regression algorithm. Construction of the model is based on a training data set obtained from 3-D simulation results, covering a range of plasma parameters of relevance to satellites in low earth orbit (LEO) at midlatitudes. The model skill is then assessed by comparing predictions with potentials in a distinct validation data set. Owing to large satellite orbital speeds, fixed bias probes would provide measurements with higher temporal and spatial resolution than possible with sweep voltage probes.

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 score0.669
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.227
Teacher spread0.207 · 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