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Depth-Dose Distribution Dependence on the Energy Profile of Linear and Laser Wakefield Accelerator Electron Beams

2021· article· en· W3203631523 on OpenAlex
Tuấn Anh Nguyễn, C. Rangacharyulu, Châu Văn Tạo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACOW · 2021
Typearticle
Languageen
FieldEngineering
TopicPhotocathodes and Microchannel Plates
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLinear particle acceleratorElectronPhysicsLaserDistribution (mathematics)Energy distributionNuclear physicsEnergy (signal processing)Plasma accelerationAtomic physicsComputational physicsOpticsBeam (structure)MathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

The depth-dose distributions of 10 MeV electron beams used for food irradiation and sterilization purposes at Research and Development Center for Radiation Technology, HCMC, Vietnam are measured and the results are well reproduced by the MCNP simulations. We extend the simulations to predict the dose depth distribution for 10 MeV electron beams with the energy profiles of a model Laser Wake Field accelerator (LWFA). The dosimetry and simulation results show that the maximum dose of the depth-dose curve inside the product is 1.4 times surface dose with an area density limit of 8.6 g/cm² for two-sided irradiation with nearly mono-energetic beams from the linear accelerator and the corresponding parameters for LWFA are 1.2 times surface dose and 13.0 g/cm², respectively.

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.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.214
Teacher spread0.203 · 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