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Record W2156223792 · doi:10.1109/pac.2007.4440631

New nonscaling FFAG for medical applications

2007· article· en· W2156223792 on OpenAlexaff
C. Johnstone, Shane Koscielniak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsCyclotronPhysicsSynchrotronMagnetProton therapyAccelerationAperture (computer memory)Nuclear physicsSuperconducting magnetParticle acceleratorProtonBeam (structure)Computational physicsNuclear magnetic resonanceOpticsAcoustics

Abstract

fetched live from OpenAlex

A hybrid design for a fixed-field alternating-gradient (FFAG) accelerator has been invented which uses edge and alternating-gradient focusing principles applied in a specific configuration to a combined-function (CF) magnet to stabilize tunes through an acceleration cycle which extends over a factor of 6 in momentum. Using normal conducting magnets, the final, extracted energy from this machine can attain slightly more than 400 MeV/nucleon without the use of superconducting elements. By using fixed-fields, the machine proposed here has the high current advantage of the cyclotron yet retains important features of the synchrotron: smaller radial aperture, variable energy, and both kicker-based and resonant extraction. This machine, without modification, supports a proton and a carbon ion beam in the energy range of interest for cancer therapy. Competing machines for this application include superconducting cyclotrons[1], synchrotrons [2], and, more recently, scaling FFAGs. As such this machine represents a broad innovation in therapy machines.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.175

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 head0.009
GPT teacher head0.263
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreMethods

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

Citations2
Published2007
Admission routes1
Has abstractyes

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