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Record W3007941237 · doi:10.1103/physrevc.102.014002

Measurement of neutron-proton capture in the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>SNO</mml:mi><mml:mo>+</mml:mo></mml:math> water phase

2020· article· lv· W3007941237 on OpenAlexafffund
Mark R. Anderson, S. Andringa, M. Askins, D. J. Auty, N. Barros, F. Barão, R. Bayes, E. W. Beier, A. Białek, S. D. Biller, R. Bonventre, M. G. Boulay, E. Caden, J. Caravaca Rodríguez, D. Chauhan, M. Chen, O. Chkvorets, B. T. Cleveland, M. A. Cox, M. M. Depatie, J. Dittmer, F. Di Lodovico, A. Earle, E. Falk, N. Fatemighomi, V. Fischer, E.R. Fletcher, R. Ford, K. Frankiewicz, K. Gilje, D. Gooding, C. Grant, J. E. Grove, A. L. Hallin, D. Hallman, S. Hans, J. Hartnell, P. J. Harvey, W. J. Heintzelman, R. L. Helmer, D. F. Horne, B. Hreljac, Jun Hu, A. S. M. Hussain, A. S. Inácio, C. Jillings, T. Kaptanoglu, P. Khaghani, J. Klein, R. Knapik, L. L. Kormos, B. Krar, C. Kraus, C. B. Krauss, Tereza Kroupova, I. Lam, Benjamin Land, A. Latorre, I. Lawson, L. Lebanowski, E. J. Leming, A. Li, J. Lidgard, B. Liggins, Yen-Hsun Lin, Y. Liu, V. Lozza, M. Luo, Simon Maguire, S. Manecki, J. Maneira, R. D. Martin, E. Marzec, A. Mastbaum, N. McCauley, A.B. McDonald, Pawel Mekarski, M. Meyer, C. Mills, I. Morton-Blake, S. Nae, M. Nirkko, L. J. Nolan, H. M. O’Keeffe, G. D. Orebi Gann, M. J. Parnell, J. Paton, S. J. M. Peeters, T. Pershing, L. Pickard, G. Prior, A. Reichold, S. Riccetto, R. Richardson, M. Rigan, J. Rose, R. Rosero, P. M. Rost, J. Rumleskie, I. Semenec, F. Shaker, Manoj Kumar Sharma, K. Singh, P. Skensved, M. Smiley, M. Stringer, R. Svoboda, B. Tam, Liyan Tian, J. C-L. Tseng, E. Turner, R. Van Berg, J. G. C. Veinot, C.J. Virtue, E. Vázquez-Jáuregui, S. C. Walton, Jiu‐Yao Wang, M. Ward, Jan J. Weigand, J. R. Wilson, P. Woosaree, A. Wright, M. Yeh, T. Zhang, Yingdi Zhang, Κ. Zuber, A. Zummo

Bibliographic record

VenuePhysical review. C · 2020
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsTRIUMFLaurentian UniversityUniversity of AlbertaQueen's University
FundersNuclear PhysicsBasic Energy SciencesOntario Ministry of Research and InnovationFundação para a Ciência e a TecnologiaScience and Technology Facilities CouncilNational Nuclear Security AdministrationUniversity of California BerkeleyOffice of ScienceSimon Fraser UniversityConsejo Nacional de Ciencia y TecnologíaHigh Energy PhysicsDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoMarie CurieDeutsche ForschungsgemeinschaftCanada Foundation for InnovationOntario Ministry of Research, Innovation and ScienceQueen's UniversityWestern Canada Research GridEuropean CommissionUniversity of AlbertaNational Research Council CanadaEuropean Research CouncilSeventh Framework ProgrammeStrongNorthern Ontario Heritage Fund CorporationNatural Sciences and Engineering Research Council of CanadaFermilabNational Science FoundationCompute CanadaCanadian Institute for Advanced ResearchU.S. Department of Energy
KeywordsNeutronNeutron capturePhysicsProtonNuclear physicsNeutron temperatureCherenkov radiationDetectorAnalytical Chemistry (journal)ChemistryOptics

Abstract

fetched live from OpenAlex

The $\mathrm{SNO}+$ experiment collected data as a low-threshold water Cherenkov detector from September 2017 to July 2019. Measurements of the 2.2-MeV $\ensuremath{\gamma}$'s produced by neutron capture on hydrogen were made using an Am-Be calibration source, for which a large fraction of emitted neutrons are produced simultaneously with a 4.4-MeV $\ensuremath{\gamma}$. Analysis of the delayed coincidence between the 4.4-MeV $\ensuremath{\gamma}$ and the 2.2-MeV capture $\ensuremath{\gamma}$ revealed a neutron detection efficiency that is centered around 50% and varies at the level of 1% across the inner region of the detector, which to our knowledge is the highest efficiency achieved among pure water Cherenkov detectors. In addition, the neutron capture time constant was measured and converted to a thermal neutron-proton capture cross section of $336.{3}_{\ensuremath{-}1.5}^{+1.2}\phantom{\rule{4pt}{0ex}}\mathrm{mb}$.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.039
GPT teacher head0.306
Teacher spread0.267 · 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.

Study designTheoretical or conceptual
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

Citations15
Published2020
Admission routes2
Has abstractyes

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