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Record W2964107613 · doi:10.1103/physrevc.71.034607

Model-independent tracking of criticality signals in nuclear multifragmentation data

2005· article· en· W2964107613 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysical Review C · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStatistical Mechanics and Entropy
Canadian institutionsUniversité Laval
FundersRégion NormandieCentre National de la Recherche Scientifique
KeywordsPhysicsScalingCriticalityHeavy ionRange (aeronautics)Nuclear physicsFunction (biology)Statistical physicsEvent (particle physics)Energy (signal processing)Self-organized criticalityIonQuantum mechanics

Abstract

fetched live from OpenAlex

We look for signals of criticality in multifragment production in heavy-ion collisions using model-independent universal fluctuations theory. The phenomenon is studied as a function of system size, bombarding energy, and impact parameter over a wide range of INDRA data. For very central collisions $(b/{b}_{\mathrm{max}}<0.1)$ we find evidence that the largest fragment in each event, ${Z}_{\mathrm{max}}$, plays the role of an order parameter, defining two different regimes at low and high incident energy, respectively, according to the scaling properties of its fluctuations. Data for a wide range of system masses and incident energies collapse on to an approximately universal scaling function in each regime for the most central collisions. The forms of the scaling functions for the two regimes are established, and their dependence on the total mass and the bombarding energy is mapped out. Data suggest that these regimes are linked to the disappearance of heavy residues in central collisions.

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.

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 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 score0.961
Threshold uncertainty score0.360

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)0.0000.000

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 head0.089
GPT teacher head0.399
Teacher spread0.310 · 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