MétaCan
Menu
Back to cohort
Record W2766562615 · doi:10.1016/j.phpro.2017.09.061

A Low-cost Beam Profiler Based On Cerium-doped Silica Fibers

2017· article· en· W2766562615 on OpenAlexaboutno aff
David Potkins, S. Braccini, Konrad P. Nesteruk, Tommaso Stefano Carzaniga, A. Vedda, N. Chiodini, Jacob Timmermans, Stéphane Melanson, Morgan Dehnel

Bibliographic record

VenuePhysics Procedia · 2017
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsnot available
FundersUniversità degli Studi di Milano-BicoccaUniversity of Bern
KeywordsLaser beam qualityBeam (structure)Materials scienceOpticsIon beamRange (aeronautics)PhysicsParticle beamBeam diameterOptical fiberLaser

Abstract

fetched live from OpenAlex

A beam profiler called the Universal Beam Monitor (UniBEaM) has been developed by D-Pace Inc. (Canada) and the Albert Einstein Center for Fundamental Physics, Laboratory for High Energy Physics, University of Bern (Switzerland). The device is based on passing 100 to 600 micron cerium-doped optical fibers through a particle beam. Visible scintillation light from the sensor fibers is transmitted over distances of tens of meters to the light sensors with minimal signal loss and no susceptibility to electromagnetic fields. The probe has an insertion length of only 70 mm. The software plots the beam intensity distribution in the horizontal and vertical planes, and calculates the beam location and integrated profile area, which correlates well with total beam current. UniBEaM has a large dynamic range, operating with beam currents of ∼pA to mA, and a large range of particle kinetic energies of ∼keV to GeV, depending on the absorbed power density. Test data are presented for H- beams at 25keV for 500 μA, and H+ beams at 18MeV for 50pA to 10 μA. Maximum absorbed power density of the optical fiber before thermal damage is discussed in relation to dE/dx energy deposition as a function of particle type and kinetic energy. UniBEaM is well suited for a wide variety of beamlines including discovery science applications, radio-pharmaceutical production, hadron therapy, industrial ion beam applications including ion implantation, industrial electron beams, and ion source testing.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.267
Teacher spread0.243 · 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

Citations25
Published2017
Admission routes1
Has abstractyes

Explore more

Same venuePhysics ProcediaSame topicFusion materials and technologiesFrench-language works237,207