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Record W2134535409 · doi:10.1063/1.1525869

A low-energy charged particle distribution imager with a compact sensor for space applications

2003· article· en· W2134535409 on OpenAlexaff
D. J. Knudsen, J. K. Burchill, K.‐J. Berg, Taylor Cameron, Greg Enno, Clifford G. Marcellus, E. P. King, Ivan Wevers, Robert A. King

Bibliographic record

VenueReview of Scientific Instruments · 2003
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIconComputer scienceCitationInformation retrievalEnergy (signal processing)Space (punctuation)World Wide WebComputer graphics (images)PhysicsOperating system

Abstract

fetched live from OpenAlex

Low-energy plasmas having temperatures of order 1 eV or less are found commonly in the ionospheres and space environments of Earth and other planets. Measuring the density, temperature, drift velocities, phase-space anisotropies, and other properties of these plasmas presents numerous challenges. Examples are distortions of particle trajectories due to spacecraft wakes, spacecraft charging, and particle gyromotion in magnetized plasmas. Furthermore, these plasmas are known to organize into structures as small as tens of meters across, traversed by spacecraft in tens of milliseconds or less. The Suprathermal Plasma Imager (SPI) was developed to address these challenges. The SPI is optimized for measurements of particles with ∼1 eV energies, and of the suprathermal extension of those populations up to several hundred eV. The SPI is sensitive to particle flux intensities of order 6×105 cm−2 s−1 sr−1 eV−1 and greater. It produces 3024-pixel images corresponding to two-dimensional (angle/energy) cuts through plasma velocity distribution functions, with an image frame rate of up to 100 s−1. The SPI has a cylindrical sensor head measuring 37.5 mm in diameter and 14 cm long, with a mass of 350 g. The relatively small size and mass of the sensor allow it to be deployed easily on a boom, outside of the spacecraft’s electrical sheath and in a region where wake perturbations are reduced. The SPI sensor head contains no electronic circuitry, but instead creates a visible image of the particle distribution with a system of dc-biased grids, microchannel plates, and a phosphor screen. The phosphor image is transferred via an imaging fiber-optic cable to an instrument box in the main spacecraft body, where it is sampled with a charge-coupled device and support electronics. Inside the sensor, angle/energy images of incident particle distributions are formed by a pair of concentric hemispherical grids. The incident energies Ei accessible to the analyzer lie in the range 0⩽Ei⩽Emax where Emax≈qΔV/3, ΔV being the potential difference between the hemispheres. For an ideal analyzer, energy resolution ΔE/E is ⩽22% over most of the imaged energy range, degrading at energies below Emax/10. Angular resolution varies from 2° to 8° full width at half maximum between Emax and Emax/10. Energy and angular resolutions are degraded in the presence of a potential difference between the sensor and surrounding plasma. A 37.5-mm-diam version of the analyzer with a 0.86-mm-wide aperture has an ideal energy-dependent geometry factor of ≈5×10−4 eV sr cm2 for a square detector pixel of width 0.28 mm. Laboratory testing shows degraded energy resolution compared to ideal values, due in part to particle scattering within the analyzer. The SPI was tested successfully in flight on the GEODESIC auroral sounding rocket on 26 February 2000.

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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.004

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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

Citations40
Published2003
Admission routes1
Has abstractyes

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