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Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay

2023· article· en· W4366681637 on OpenAlexaff
Fengpeng An, A. B. Balantekin, M. Bishai, S. Blyth, G. F. Cao, Jun Cao, Jin Chang, Y. Chang, H. S. Chen, H. Y. Chen, S. M. Chen, Y. Chen, Y. X. Chen, Z. Y. Chen, Jie Cheng, Z. K. Cheng, J. J. Cherwinka, M. C. Chu, J. P. Cummings, Olivia Dalager, F. S. Deng, Y. Y. Ding, X. Y. Ding, M. Diwan, Tadeáš Dohnal, Dmitry Dolzhikov, J. Dove, H. Y. Duyang, D. A. Dwyer, J. P. Gallo, M. Gonchar, G. H. Gong, Haipeng Gong, W. Gu, J. Y. Guo, Lei Guo, X. H. Guo, Yuhang Guo, Ziyi Guo, R. Hackenburg, Yang Han, S. Hans, M. He, K. M. Heeger, Y. K. Heng, Y. K. Hor, Y. Hsiung, Beibei Hu, Jun Hu, T. Hu, Zhongfa Hu, H. X. Huang, J. H. Huang, X. T. Huang, Y. B. Huang, Patrick Huber, D. E. Jaffe, K. L. Jen, X. L. Ji, Xingzhao Ji, R. A. Johnson, D. Jones, Li-Wei Kang, S. H. Kettell, S. Kohn, M. Krämer, T. J. Langford, J. Lee, J. H. C. Lee, R. T. Lei, R. Leitner, J. K. C. Leung, F. Li, H. L. Li, Jinjing Li, Q. J. Li, R. H. Li, S. Li, S. C. Li, W. D. Li, X. N. Li, X. Q. Li, Yufeng Li, Z. B. Li, H. Liang, C.-J. Lin, Guey-Lin Lin, S. Lin, J. J. Ling, J. M. Link, L. Littenberg, B. R. Littlejohn, J. C. Liu, J. L. Liu, J. X. Liu, C. Lu, H. Q. Lu, K. B. Luk, B. Z., X. B., X. Y., Y. Q., R. C. Mandujano, C. Marshall, Kirk T. McDonald, R. D. McKeown, Yue Meng, J. Napolitano, D. Naumov, E. Naumova, T. M. T. Nguyen, J. P. Ochoa‐Ricoux, A. Olshevskiy, Hsiao-Ru Pan, J. Park, S. Patton, J. C. Peng, C. S. J. Pun, F. Z. Qi, M. Qi, X. Qian, N. Raper, Jie Ren, C. Morales Reveco, R. Rosero, B. Roskovec, Xichao Ruan, B. Russell, H. Steiner, Jian Sun, Tomáš Tměj, Konstantin Treskov, W.-H. Tse, C. E. Tull, B. Viren, V. Vorobel, Chunhong Wang, Jun Wang, M. Wang, N. Y. Wang, R. G. Wang, W. Wang, X. Wang, Y. Wang, Y. F. Wang, Z. Wang, Zhe Wang, H. Wei, L. H. Wei, W. Wei, Liangjian Wen, K. Whisnant, C. G. White, H. L. H. Wong, E. Worcester, D. R. Wu, Q. Wu, W. Wu, D. M. Xia, Z. Q. Xie, Z. Z. Xing, Huaiyu Xu, Jinliang Xu, T. Xu, T. Xue, C. G. Yang, L. Yang, Yuhao Yang, H. F. Yao, M. Ye, M. Yeh, Ben Young, H. Z. Yu, Zeyuan Yu, Bochun Yue, Vitalii Zavadskyi, S. Zeng, Yuda Zeng, Liang Zhan, C. Zhang, F. Y. Zhang, H. H. Zhang, J. L. Zhang, J. W. Zhang, Qingmin Zhang, S. Q. Zhang, Xueyao Zhang, Y. M. Zhang, Y. X. Zhang, Y. Y. Zhang, Z. J. Zhang, Z. P. Zhang, Z. Y. Zhang, J. Y. Zhao, R. Z. Zhao, Li Zhou, H. L. Zhuang, J. H. Zou

Bibliographic record

VenuePhysical Review Letters · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsInstitute of Particle Physics
FundersJoint Institute for Nuclear ResearchResearch Grants Council, University Grants CommitteeMinisterstvo Školství, Mládeže a TělovýchovyChinese Academy of SciencesGovernment of Guangdong ProvinceNational Natural Science Foundation of ChinaChina RailwayShenzhen GovernmentNational Science and Technology Major ProjectUniverzita Karlova v PrazeCAS Center for Excellence in Particle PhysicsMinistry of EducationU.S. Department of EnergyNational Science Foundation
KeywordsPhysicsOscillation (cell signaling)NeutrinoCalibrationNuclear physicsMixing (physics)NeutronNeutrino oscillationInverse

Abstract

fetched live from OpenAlex

We present a new determination of the smallest neutrino mixing angle θ_{13} and the mass-squared difference Δm_{32}^{2} using a final sample of 5.55×10^{6} inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample is selected from the complete dataset obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are sin^{2}2θ_{13}=0.0851±0.0024, Δm_{32}^{2}=(2.466±0.060)×10^{-3} eV^{2} for the normal mass ordering or Δm_{32}^{2}=-(2.571±0.060)×10^{-3} eV^{2} for the inverted mass ordering.

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)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.038
GPT teacher head0.327
Teacher spread0.289 · 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

Citations70
Published2023
Admission routes1
Has abstractyes

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