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Initial Results from the Majorana Demonstrator

2017· article· en· W2528569341 on OpenAlexaff
S. R. Elliott, N. Abgrall, I. J. Arnquist, F. T. Avignone, A. S. Barabash, F. E. Bertrand, A. W. Bradley, V. Brudanin, M. Busch, M. Buuck, T. S. Caldwell, Y-D. Chan, C. D. Christofferson, P.-H. Chu, C. Cuesta, J. A. Detwiler, C. Dunagan, Y. V. Efremenko, H. Ejiri, A. Fullmer, A. Galindo-Uribarri, T. Gilliss, G. K. Giovanetti, M. P. Green, J. Gruszko, I. S. Guinn, V. E. Guiseppe, R. Henning, E. W. Hoppe, M. A. Howe, B.R. Jasinski, K. Keeter, M. F. Kidd, С. И. Коновалов, R. T. Kouzes, J. Leon, A.M. Lopez, J. MacMullin, R. D. Martin, R. Massarczyk, S. J. Meijer, S. Mertens, J. L. Orrell, C. O’Shaughnessy, A. W. P. Poon, D. C. Radford, J. Rager, K. Rielage, R. G. H. Robertson, E. Romero-Romero, B. Shanks, M. Shirchenko, A. M. Suriano, D. Tedeschi, J. E. Trimble, R. L. Varner, S. Vasilyev, K. Vetter, K. Vorren, B. R. White, J. F. Wilkerson, C. Wiseman, W. Xu, E. Yakushev, C.-H. Yu, V. Yumatov, I. Zhitnikov

Bibliographic record

VenueJournal of Physics Conference Series · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsQueen's University
FundersLos Alamos National LaboratoryNuclear PhysicsLaboratory Directed Research and DevelopmentU.S. Department of EnergyOffice of ScienceRussian Foundation for Basic ResearchNational Science Foundation
KeywordsMAJORANADouble beta decayNeutrinoParticle physicsPhysicsDetectorSterile neutrinoScalabilityNuclear physicsNeutrino oscillationComputer scienceOperating systemOptics

Abstract

fetched live from OpenAlex

Neutrinoless double-beta decay searches seek to determine the nature of neutrinos, the existence of a lepton violating process, and the effective Majorana neutrino mass. The M ajorana Collaboration is assembling an array of high purity Ge detectors to search for neutrinoless double-beta decay in 76 Ge. The M ajorana D emonstrator is composed of 44.8 kg (29.7 kg enriched in 76 Ge) of Ge detectors in total, split between two modules contained in a low background shield at the Sanford Underground Research Facility in Lead, South Dakota. The initial goals of the D emonstrator are to establish the required background and scalability of a Ge-based, next-generation, tonne-scale experiment. Following a commissioning run that began in 2015, the first detector module started physics data production in early 2016. We will discuss initial results of the Module 1 commissioning and first physics run, as well as the status and potential physics reach of the full M ajorana D emonstrator experiment. The collaboration plans to complete the assembly of the second detector module by mid-2016 to begin full data production with the entire array.

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)0.009
metaresearch head score (Gemma)0.005
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 score0.013
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.009

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 head0.063
GPT teacher head0.335
Teacher spread0.271 · 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".

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Citations28
Published2017
Admission routes1
Has abstractyes

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