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Record W2759367060 · doi:10.1103/physrevc.98.044611

New “3D calorimetry” of hot nuclei

2018· article· en· W2759367060 on OpenAlexaff
E. Vient, L. Manduci, E. Legouée, L. Augey, É. Bonnet, B. Borderie, R. Bougault, A. Chbihi, D. Dell’Aquila, Q. Fable, L. Francalanza, J. D. Frankland, E. Galichet, D. Gruyer, D. Guinet, M. Henri, M. La Commara, G. Lehaut, N. Le Neindre, I. Lombardo, O. Lopez, P. Marini, M. Pârlog, M. F. Rivet, E. Rosato, R. Roy, P. St-Onge, G. Spadaccini, G. Verde, M. Vigilante

Bibliographic record

VenuePhysical review. C · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsProjectileNucleusDetectorEvent (particle physics)CollisionDomain (mathematical analysis)Selection (genetic algorithm)Quality (philosophy)Fermi Gamma-ray Space TelescopeEnergy (signal processing)Nuclear physicsComputer sciencePhysicsComputational physicsBiological systemNuclear engineeringMaterials scienceAlgorithmMathematicsArtificial intelligenceOpticsEngineeringBiology

Abstract

fetched live from OpenAlex

In the Fermi energy domain, it is extremely complex to experimentally isolate fragments and particles emitted by a hot nucleus produced during a heavy ion collision. This article presents a new method to characterize more precisely hot quasiprojectiles. It tries to take into account as accurately as possible the distortions generated by all the other potential participants of the nuclear reaction. It is quantitatively shown that this method is an improvement compared to a ``classical calorimetry'' used with a $4\ensuremath{\pi}$ detector array.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.027
GPT teacher head0.376
Teacher spread0.349 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations5
Published2018
Admission routes1
Has abstractyes

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