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Record W2473448366 · doi:10.1139/cjp-2016-0184

Centrality dependence of total disintegration of target nuclei in high energy nucleus–nucleus interactions

2016· article· en· W2473448366 on OpenAlexvenueno aff
Swarnapratim Bhattacharyya, Maria Haiduc, Alina Tania Neagu, Elena Firu

Bibliographic record

VenueCanadian Journal of Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsnot available
Fundersnot available
KeywordsMultiplicity (mathematics)PhysicsProjectileNucleusNuclear physicsCentralityFragmentation (computing)Atomic physicsGeometryStatistics

Abstract

fetched live from OpenAlex

A study of centrality dependence of target fragmentation and multiparticle production has been carried out in 16 O–AgBr, 22 Ne–AgBr, and 28 Si–AgBr interactions at 4.1–4.5 AGeV/c for the total disintegrated (TD) events. Average multiplicity of black particles increases linearly with decreasing centrality while average multiplicity of grey and shower particles decreases with decreasing centrality for the TD events. The decrease of average multiplicity of grey particles is linear; on the other hand, in the case of shower particles, the increase is nonlinear. With the increase of the mass of the projectile beam, the average multiplicity of black particles decreases and the average multiplicity of grey particles increases for the TD events. This observation has been explained on the basis of the fireball model; however, in the case of shower particles, average multiplicity increases with increase of projectile mass.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.979

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations6
Published2016
Admission routes1
Has abstractyes

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