MétaCan
Menu
Back to cohort
Record W3034234331 · doi:10.1016/j.nima.2020.164657

Positron production using a 9 MeV electron linac for the GBAR experiment

2020· article· en· W3034234331 on OpenAlexaff
M. Charlton, J.J. Choi, М. Chung, Pierre Cladé, P. Comini, P.-P. Crépin, P. Crivelli, O. D. Dalkarov, P. Debu, L. Dodd, A. Douillet, Saïda Guellati-Khélifa, Paul-Antoine Hervieux, Laurent Hilico, A. Husson, P. Indelicato, Gianluca Janka, S. Jonsell, Jean‐Philippe Karr, B.H. Kim, E.-S. Kim, S.K. Kim, Y. Ko, Tymoteusz Kosiński, N. Kuroda, B. M. Latacz, Hyorim Lee, Jeehyun Lee, A.M.M. Leite, K. Lévêque, E. Lim, L. Liszkay, P. Lotrus, Thomas Louvradoux, D. Lunney, Giovanni Manfredi, B. Mansoulié, M. Matusiak, G. Mornacchi, V. V. Nesvizhevsky, F. Nez, S. Niang, Reo Nishi, S. Nourbaksh, Kang Hyun Park, N. Paul, P. Pérez, S. Procureur, B. Radics, C. Regenfus, J.M. Rey, J.-M. Reymond, Serge Reynaud, J.-Y. Roussé, Olivier Rousselle, A. Rubbia, J. Rzadkiewicz, Y. Sacquin, F. Schmidt–Kaler, M. Staszczak, B. Tuchming, B. Vallage, A. Voronin, A. Welker, D. P. van der Werf, S. Wolf, D. Won, S. Wronka, Y. Yamazaki, K.H. Yoo

Bibliographic record

VenueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment · 2020
Typearticle
Languageen
FieldEngineering
TopicMuon and positron interactions and applications
Canadian institutionsInstitute of Particle Physics
FundersSorbonne UniversitéCentre National de la Recherche ScientifiqueUniversité de Recherche Paris Sciences et LettresEidgenössische Technische Hochschule ZürichNational Research Foundation of KoreaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungCentre National d’Etudes SpatialesMinistry of EducationAgence Nationale de la RechercheCERN
KeywordsNuclear physicsPositronLinear particle acceleratorPhysicsProduction (economics)Nuclear engineeringElectronMedical physicsBeam (structure)EngineeringOpticsEconomics

Abstract

fetched live from OpenAlex

For the GBAR (Gravitational Behaviour of Antihydrogen at Rest) experiment at CERN’s Antiproton Decelerator (AD) facility we have constructed a source of slow positrons, which uses a low-energy electron linear accelerator (linac). The driver linac produces electrons of 9 MeV kinetic energy that create positrons from bremsstrahlung-induced pair production. Staying below 10 MeV ensures no persistent radioactive activation in the target zone and that the radiation level outside the biological shield is safe for public access. An annealed tungsten-mesh assembly placed directly behind the target acts as a positron moderator. The system produces 5×107 slow positrons per second, a performance demonstrating that a low-energy electron linac is a superior choice over positron-emitting radioactive sources for high positron flux.

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)0.002
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.090
GPT teacher head0.407
Teacher spread0.318 · 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

Citations18
Published2020
Admission routes1
Has abstractno

Explore more

Same venueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated EquipmentSame topicMuon and positron interactions and applicationsFrench-language works237,207