MétaCan
Menu
Back to cohort
Record W2390113820

Analysis of Multi-Particle Production at SPS and RHIC by Two-Source Statistical Model

2002· article· en· W2390113820 on OpenAlexaff
Lu Zhong

Bibliographic record

VenueHigh Energy Physics and Nuclear Physics · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsPhysicsHadronizationRapiditySource modelProjectileCollisionParticle (ecology)Nuclear physicsStatistical modelComputational physicsLarge Hadron ColliderStatistics
DOInot available

Abstract

fetched live from OpenAlex

The data of multi-particle production in 158 A GeV Pb+Pb collisions and (?)s =130 A GeV Au+Au collisions are analyzed by two-source statistical model. It is found that in 158 A GeV Pb+Pb collisions the source is composed of a hot, small inner part and a large, cool outer part. The outer part characterizes the projectile-like and target-like, and the inner part characterizes the central reaction zone. In (?)s =130 A GeV Au+Au collisions, there is a much hotter and larger inner source. The temperature is at least 15MeV higher than that in the inner source in 158 A GeV Pb+Pb collisions. The volume is at least two times of that in the later collision. The reason is that the (?)s =130 A GeV Au+Au collision has large rapidity region [-4.9,4.9], while the experimental data are taken from a small pseudo-rapidity region, |η|0.5 in which the particles are uniformly distributed as a single source. For a source formed with uniformly-distributed particles, both the single-source statistical model and the two-source statistical model are available, while for a source formed with non-uniformly-distributed particles, only the two-source statistical model is available. The RHIC can provide a hot and large inner source that may be formed in the early stage of hadronization from QGP and may have important physical content behind. We suggest to make synchronous measurement in the outer region, e.g. 3|y|4, so as to make comparison.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.251
Teacher spread0.232 · 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 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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueHigh Energy Physics and Nuclear PhysicsSame topicHigh-Energy Particle Collisions ResearchFrench-language works237,207