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New Measurements of High-Momentum Nucleons and Short-Range Structures in Nuclei

2012· article· en· W2109141223 on OpenAlexaff
N. Fomin, J. Arrington, R. Asaturyan, F. Benmokhtar, W. Boeglin, P. Bosted, A. Bruell, M. H. S. Bukhari, M. E. Christy, E. Chudakov, B. Clasie, S. H. Connell, M. M. Dalton, A. V. Daniel, Donal B. Day, D. Dutta, R. Ent, L. El Fassi, H. Fenker, B. W. Filippone, K. Garrow, D. Gaskell, C. Hill, R. J. Holt, T. Horn, M. K. Jones, J. Jourdan, N. Kalantarians, C. Keppel, D. Kiselev, M. Kotulla, R. Lindgren, A. Lung, S. Malace, P. Markowitz, P. McKee, D. G. Meekins, H. Mkrtchyan, T. Navasardyan, G. Niculescu, A. K. Opper, C. F. Perdrisat, D. H. Potterveld, V. Punjabi, X. Qian, P. E. Reimer, J. Roche, V. M. Rodriguez, O. Rondon, Eva C. Schulte, J. Seely, E. Segbefia, K. Slifer, G. R. Smith, P. Solvignon, V. Tadevosyan, S. Tajima, L. Tang, G. Testa, R. Trojer, V. Tvaskis, W. Vulcan, C. Wasko, F. R. Wesselmann, S. A. Wood, J. Wright, Xiaochao Zheng

Bibliographic record

VenuePhysical Review Letters · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsTRIUMF
FundersThomas Jefferson National Accelerator FacilityU.S. Department of EnergyNational Science Foundation
KeywordsNucleonPhysicsMomentum (technical analysis)Nuclear physicsRange (aeronautics)ScatteringKinematicsParticle physicsClassical mechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

We present new measurements of electron scattering from high-momentum nucleons in nuclei. These data allow an improved determination of the strength of two-nucleon correlations for several nuclei, including light nuclei where clustering effects can, for the first time, be examined. The data also include the kinematic region where three-nucleon correlations are expected to dominate.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.331
Teacher spread0.287 · 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 designObservational
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

Citations190
Published2012
Admission routes1
Has abstractyes

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