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Record W4319962160 · doi:10.1063/5.0127272

The atmospheric X-ray imaging spectrometer (AXIS) instrument: Quantifying energetic particle precipitation through bremsstrahlung X-ray imaging

2023· article· en· W4319962160 on OpenAlexaff
Grant Berland, Robert A. Marshall, Clara M. St. Martin, Joseph Buescher, Richard Kohnert, Spencer Boyajian, C. M. Cully, M. McCarthy, Wei Xu

Bibliographic record

VenueReview of Scientific Instruments · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
FundersHeliophysics Division
KeywordsCadmium zinc tellurideSpectrometerPhysicsBremsstrahlungOpticsPhotonElectromagnetic shieldingSynchrotron radiationDetector

Abstract

fetched live from OpenAlex

The Atmospheric X-ray Imaging Spectrometer (AXIS) described in this work is a compact, wide field-of-view, hard x-ray imager. The AXIS instrument will fly onboard the Atmospheric Effects of Precipitation through Energetic X-rays (AEPEX) 6U CubeSat mission and will measure bremsstrahlung x-ray photons in the 50-240 keV range with cadmium-zinc-telluride (CZT) detectors using coded aperture optics. AXIS will measure photons generated by energetic particle precipitation for the purpose of determining the spatial scales of precipitation and estimating electron precipitation characteristics. This paper describes the design and testing of the AXIS instrument, including a summary of simulations performed that motivate the shielding, optics, and mechanical design. Testing and characterization is reported that validates the instrument design and shows that the instrument design meets or exceeds the measurement requirements necessary for AEPEX mission success.

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 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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.017
GPT teacher head0.269
Teacher spread0.253 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations5
Published2023
Admission routes1
Has abstractyes

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