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Monitoring the SNS basement neutron background with the MARS detector

2022· article· en· W4220685123 on OpenAlexaff
D. Akimov, Peng An, C. Awe, P. S. Barbeau, Bruce Becker, V. Belov, I. Bernardi, M. A. Blackston, C. Bock, A. Bolozdynya, J. Browning, Belkis Cabrera-Palmer, D. Chernyak, E. Conley, J. Daughhetee, J. A. Detwiler, K. Ding, M. Durand, Yu. Efremenko, S. R. Elliott, L. Fabris, M. Febbraro, A. Gallo Rosso, A. Galindo-Uribarri, M. P. Green, M. R. Heath, S. Hedges, D. Hoang, M. Hughes, T. Johnson, А. В. Хромов, A. M. Konovalov, E. Kozlova, A. Kumpan, L. Li, J. M. Link, J. Liu, Kulwinder Singh Mann, D. M. Markoff, J. Mastroberti, P. E. Mueller, J. Newby, D. S. Parno, S. Penttilä, D. Pershey, R. Rapp, H. Ray, J. Raybern, O. Razuvaeva, D. Reyna, G. C. Rich, J. Ross, D. Rudik, J. Runge, D. J. Salvat, A. M. Salyapongse, K. Scholberg, A. Shakirov, G. Simakov, G. Sinev, W. M. Snow, V. Sosnovstsev, B. Suh, R. Tayloe, K. Tellez-Giron-Flores, I. Tolstukhin, E. Ujah, J. Vanderwerp, R. L. Varner, C. J. Virtue, G. Visser, T. Wongjirad, Y.-R. Yen, J. Yoo, C.-H. Yu, J. Zettlemoyer, Ben A. Johnson

Bibliographic record

VenueJournal of Instrumentation · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsLaurentian University
FundersOak Ridge National LaboratoryHigh Energy PhysicsNuclear PhysicsOak Ridge Institute for Science and EducationInstitute for Basic ScienceMinistry of Science and Higher Education of the Russian FederationOffice of ScienceRussian Foundation for Basic ResearchSandia National LaboratoriesNational Nuclear Security AdministrationU.S. Department of EnergyEuropean CommissionSwarthmore CollegeOak Ridge Associated UniversitiesNational Science Foundation
KeywordsMars Exploration ProgramNeutronPhysicsDetectorNuclear physicsNeutron detectionSpallation Neutron SourceOak Ridge National LaboratoryNeutrinoSpallationOpticsAstronomy

Abstract

fetched live from OpenAlex

Abstract We present the analysis and results of the first dataset collected with the MARS neutron detector deployed at the Oak Ridge National Laboratory Spallation Neutron Source (SNS) for the purpose of monitoring and characterizing the beam-related neutron (BRN) background for the COHERENT collaboration. MARS was positioned next to the COH-CsI coherent elastic neutrino-nucleus scattering detector in the SNS basement corridor. This is the basement location of closest proximity to the SNS target and thus, of highest neutrino flux, but it is also well shielded from the BRN flux by infill concrete and gravel. These data show the detector registered roughly one BRN per day. Using MARS' measured detection efficiency, the incoming BRN flux is estimated to be 1.20 ± 0.56 neutrons/m^2/MWh for neutron energies above ∼3.5 MeV and up to a few tens of MeV. We compare our results with previous BRN measurements in the SNS basement corridor reported by other neutron detectors.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.345

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 head0.022
GPT teacher head0.291
Teacher spread0.268 · 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 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

Citations6
Published2022
Admission routes1
Has abstractyes

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