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Record W2592665979 · doi:10.1139/cjp-2016-0548

Study of phase transition and its dependence on target excitation using fractal properties of pionization process

2017· article· en· W2592665979 on OpenAlexvenueno aff
Ruma Saha, Argha Deb, Dipak Ghosh

Bibliographic record

VenueCanadian Journal of Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsMultifractal systemExcitationFractalPhase transitionPionFormalism (music)Condensed matter physicsParticle physicsQuantum mechanicsMathematical analysis

Abstract

fetched live from OpenAlex

In the present work, phase transition and its dependence on target excitation in terms of Levy index and Ginzburg–Landau formalism using fractal properties of pionization process have been studied in 16O–AgBr and 32S–AgBr interactions at incident energies of 60 and 200 AGeV, respectively. For this purpose, the pion data are divided into three sets depending upon the number of grey tracks (ng). Two multifractal moments, namely, G-moment and Takagi moment, have been used as analyzing tools. The study reveals that the pion density distribution possesses multifractal structure for the two types of interactions and at all degrees of target excitation. Different types of phase transitions (thermal and non-thermal) at different energies are indicated by the data but no signal of quark–gluon plasma (QGP) phase transition is obtained.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.335
Teacher spread0.272 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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