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Status of the High Intensity Proton Beam Facility at LNL

2017· article· en· W2611130677 on OpenAlexaboutno aff
M. Maggiore, Piergiorgio Antonini, D. Benini, G. Bisoffi, Enrico Boratto, M. Calderolla, Andrea Calore, D. Campo, Nicoletta Ciatara, Juan Esposito, P. Favaron, A. Lombardi, Lorenzo Pranovi, G. Prete, L. Sarchiapone, D. Scarpa, D. Zafiropoulos, Luca de Ruvo

Bibliographic record

VenueJACOW · 2017
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsIntensity (physics)ProtonBeam (structure)Environmental scienceNuclear physicsPhysicsOptics

Abstract

fetched live from OpenAlex

In 2013 the SPES (Selective Production of Exotic Species) project has entered in the construction phase at Laboratori Nazionali di Legnaro (LNL). The project, whose main goal is the research in nuclear physics with Radioactive Beams, has foreseen the construction of a new building hosting the accelerator able to deliver protons up the energy of 70 MeV and 50kW of beam power to be used as a primary beam for the ISOL source and for a production beam for other applications. The new facility design has been expanded and upgraded for taking advantage of the dual simultaneous extraction of beams from the Cyclotron in order to provide a multipurpose high intensity irradiation facility. Today the new facility is partially installed and the Cyclotron supplied by BEST Theratronics company (CANADA) with the related beam transport lines are under commissioning. The status of the commissioning of the high power accelerator and the capabilities of the facility as multipurpose high intensity proton beam laboratory will be presented.

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)0.007
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0030.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0220.008

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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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 designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

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