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Record W4410427018 · doi:10.1103/k9tj-jq8s

Charge Pickup Reaction Cross Section for Neutron-Rich <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>p</mml:mi> </mml:mrow> </mml:math> -Shell Isotopes at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mn>900</mml:mn> <mml:mrow> <mml:mi>A</mml:mi> </mml:mrow> <mml:mtext> </mml:mtext> <mml:mtext> </mml:mtext> <mml:mi>MeV</mml:mi> </mml:mrow> </mml:math>

2025· article· lv· W4410427018 on OpenAlexafffund
B. Sun, I. Tanihata, S. Terashima, Feng Wang, R. Kanungo, C. Scheidenberger, F. Ameil, J. Atkinson, Y. Ayyad, S. Bagchi, D. Cortina‐Gil, I. Dillmann, A. Estradé, A. Evdokimov, F. Farinon, H. Geißel, G. Guastalla, R. Janik, S. Kaur, R. Knöbel, J. Kurcewicz, Yu. A. Litvinov, M. Marta, I. Mukha, C. Nociforo, H. J. Ong, S. Piétri, A. Prochazka, B. Sitár, P. Strmeň, M. Takechi, Junki Tanaka, J. Ramirez Vargas, H. Weick, J. S. Winfield

Bibliographic record

VenuePhysical Review X · 2025
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsDalhousie University
FundersHigher Education Discipline Innovation ProjectNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsPickupIsotopeNuclear physicsCross section (physics)Shell (structure)NeutronPhysicsCharge (physics)Neutron numberAtomic physicsNeutron cross sectionMaterials scienceNeutron scatteringParticle physicsComputer science

Abstract

fetched live from OpenAlex

We report charge pickup reaction cross sections for 24 p -shell isotopes, including Li 8 , 9 , Be 10 − 12 , B 10 , 13 − 15 , C 12 , 14 − 19 , and N 14 , 15 , 17 − 22 , measured at relativistic energies (approximately 900 A MeV ) on both hydrogen and carbon targets. For the first time, we reveal a universal rapid increase in the charge pickup cross sections of unstable projectiles with isospin asymmetry along several isotopic chains. The cross sections can be decoupled into distinct contributions from the mass number and isospin asymmetry of the projectile, highlighting the critical role of the latter, and can be formulated empirically.

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 score0.079
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0790.011

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 head0.021
GPT teacher head0.286
Teacher spread0.265 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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