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Record W4282924839 · doi:10.1063/5.0089402

Absolute calibration of Fujifilm BAS-TR image plate response to laser driven protons up to 40 MeV

2022· article· en· W4282924839 on OpenAlexfundno aff
Philip Martin, H. Ahmed, D. Doria, A. Alejo, R. J. Clarke, S. M. Ferguson, J. Fernández-Tobias, R. R. Freeman, J. Fuchs, A. Green, J. S. Green, D. Gwynne, F. Hanton, J. Jarrett, D. Jung, K. F. Kakolee, A. Krygier, C. L. S. Lewis, A. McIlvenny, P. McKenna, John T. Morrison, Z. Najmudin, K. Naughton, G. Nersisyan, P. A. Norreys, M. Notley, M. Roth, Jesús Álvarez Ruiz, C. Scullion, M. Zepf, S. H. Zhai, M. Borghesi, S. Kar

Bibliographic record

VenueReview of Scientific Instruments · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilCentral Laser Facility, Science and Technology Facilities CouncilEngineering and Physical Sciences Research CouncilQueen's UniversityQueen's University Belfast
KeywordsPhysicsCalibrationOpticsDetectorProtonRange (aeronautics)LaserEnergy (signal processing)Nuclear physicsAtomic physicsMaterials science

Abstract

fetched live from OpenAlex

Image plates (IPs) are a popular detector in the field of laser driven ion acceleration, owing to their high dynamic range and reusability. An absolute calibration of these detectors to laser-driven protons in the routinely produced tens of MeV energy range is, therefore, essential. In this paper, the response of Fujifilm BAS-TR IPs to 1-40 MeV protons is calibrated by employing the detectors in high resolution Thomson parabola spectrometers in conjunction with a CR-39 nuclear track detector to determine absolute proton numbers. While CR-39 was placed in front of the image plate for lower energy protons, it was placed behind the image plate for energies above 10 MeV using suitable metal filters sandwiched between the image plate and CR-39 to select specific energies. The measured response agrees well with previously reported calibrations as well as standard models of IP response, providing, for the first time, an absolute calibration over a large range of proton energies of relevance to current experiments.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.004

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 head0.015
GPT teacher head0.283
Teacher spread0.269 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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