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Record W4403190241 · doi:10.1063/5.0218767

In-situ relative calibration of Bragg crystals with Monte Carlo line ratio analysis

2024· article· en· W4403190241 on OpenAlexaff
Brian Kraus, E. Kriz, Shawn McPoyle, K. Atay, S. Malko, K. W. Hill, Lan Gao, P. C. Efthimion, R. Hollinger, Shoujun Wang, John G. King, S. Zahedpour, J. J. Rocca

Bibliographic record

VenueReview of Scientific Instruments · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsMcGill University
FundersPrinceton Plasma Physics LaboratoryFusion Energy Sciences
KeywordsMonte Carlo methodOpticsSpectrometerSpectral lineBandwidth (computing)Line (geometry)Spectral resolutionMaterials scienceCalibrationResolution (logic)PhysicsComputational physicsComputer science

Abstract

fetched live from OpenAlex

X-ray line emission spectra can thoroughly characterize hot plasmas, especially when line shapes and ratios convey distinct aspects of plasma conditions. However, the high spectral resolution required for observing line shapes is often at odds with the large bandwidth required to observe many line ratios across a wide spectral range. One strategy to obtain high spectral resolution over a wide bandwidth is to use multiple crystals with calibrated reflectivity so that line intensities across different crystals can be compared. Here, we explore the use of a low-resolution, wide-bandwidth mica survey spectrometer to infer relative reflectivity of two high-resolution, narrow-bandwidth quartz crystals. A Monte Carlo error analysis determines comparable x-ray line ratios measured from both spectrometers, resulting in an in situ calibration factor and associated uncertainty for the relative reflectivity of the high-resolution crystals.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.276
Teacher spread0.265 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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