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Bimodal Behavior of the Heaviest Fragment Distribution in Projectile Fragmentation

2009· article· en· W2066352840 on OpenAlexaff
E. Bonnet, D. Mercier, B. Borderie, F. Gulminelli, M. F. Rivet, B. Tamain, R. Bougault, A. Chbihi, R. Dayras, J. D. Frankland, E. Galichet, F. Gagnon-Moisan, D. Guinet, P. Lautesse, J. Łukasik, N. Le Neindre, M. Pârlog, E. Rosato, R. Roy, M. Vigilante, J. P. Wieleczko, B. Zwiegliński

Bibliographic record

VenuePhysical Review Letters · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStatistical Mechanics and Entropy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBimodalityPhysicsNucleonFragmentation (computing)Phase transitionProjectileNuclear physicsCharge (physics)Atomic physicsParticle physicsThermodynamics

Abstract

fetched live from OpenAlex

The charge distribution of the heaviest fragment detected in the decay of quasiprojectiles produced in intermediate energy heavy-ion collisions has been observed to be bimodal. This feature is expected as a generic signal of phase transition in nonextensive systems. In this Letter, we present new analyses of experimental data from Au on Au collisions at 60, 80, and 100 MeV/nucleon showing that bimodality is largely independent of the data selection procedure and of entrance channel effects. An estimate of the latent heat of the transition is extracted.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.298
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 designSimulation or modeling
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

Citations59
Published2009
Admission routes1
Has abstractyes

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