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Record W3158128998 · doi:10.1016/j.nds.2021.04.006

Development of a Reference Database for Beta-Delayed Neutron Emission

2021· article· en· W3158128998 on OpenAlexafffund
P. Dimitriou, I. Dillmann, B. Singh, V.M. Piksaikin, K. P. Rykaczewski, J. L. Taı́n, A. Algora, K. Banerjee, I. N. Borzov, D. Cano‐Ott, Satoshi Chiba, M. Fallot, Daniela Foligno, R. Grzywacz, Xiaolong Huang, T. Marketin, Futoshi Minato, G. Mukherjee, B. C. Rasco, A. A. Sonzogni, M. Verpelli, A.S. Egorov, M. Estienne, Lydie Giot, D.E. Gremyachkin, M. Madurga, E. A. McCutchan, E. Mendoza, K.V. Mitrofanov, M. Narbonne, Pablo Romojaro, A. Sánchez-Caballero, N. D. Scielzo

Bibliographic record

VenueNuclear Data Sheets · 2021
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsUniversity of VictoriaMcMaster UniversityTRIUMF
FundersLawrence Livermore National LaboratoryNatural Sciences and Engineering Research Council of CanadaNuclear PhysicsCentro de Investigaciones Energéticas, Medioambientales y TecnológicasOffice of ScienceBrookhaven National LaboratoryU.S. Department of EnergyInternational Atomic Energy AgencyMinisterio de Economía y CompetitividadRussian Science FoundationCentre National de la Recherche ScientifiqueBattelle
KeywordsFissile materialNeutronDelayed neutronNuclear dataDatabaseNuclear physicsNeutron emissionPhysicsNuclear engineeringComputer scienceNeutron temperatureEngineering

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.007
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0150.009
Science and technology studies0.0010.000
Scholarly communication0.0030.005
Open science0.0050.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.016

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 head0.056
GPT teacher head0.258
Teacher spread0.202 · 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

Citations52
Published2021
Admission routes2
Has abstractno

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