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Record W3086267882 · doi:10.1063/5.0020568

Optimization of radiochromic film stacks to diagnose high-flux laser-accelerated proton beams

2020· article· en· W3086267882 on OpenAlexafffund
C. B. Curry, Chelsea A. S. Dunning, M. Gauthier, H.-G. J. Chou, Frederico Fiúza, G. D. Glenn, Ying Y. Tsui, Magdalena Bazalova‐Carter, S. H. Glenzer

Bibliographic record

VenueReview of Scientific Instruments · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsProvincial Health Services AuthorityUniversity of VictoriaUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergyNational Science Foundation
KeywordsMaterials scienceProtonStack (abstract data type)OpticsVisibilityLaserIrradiationCalibrationScannerPhysicsNuclear physics

Abstract

fetched live from OpenAlex

Here, we extend flatbed scanner calibrations of GafChromic EBT3, MD-V3, and HD-V2 radiochromic films using high-precision x-ray irradiation and monoenergetic proton bombardment. By computing a visibility parameter based on fractional errors, optimal dose ranges and transitions between film types are identified. The visibility analysis is used to design an ideal radiochromic film stack for the proton energy spectrum expected from the interaction of a petawatt laser with a cryogenic hydrogen jet target.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.019
GPT teacher head0.272
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 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

Citations12
Published2020
Admission routes2
Has abstractyes

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