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Record W3106005007

Open Charm Production in p + p and Pb + Pb collisions at the CERN Large Hadron Collider

2014· article· en· W3106005007 on OpenAlexafffund
Miklós Gyulassy, J. Barrette, Charles Gale, M. Petrovici

Bibliographic record

VenueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences) · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsMesonLarge Hadron ColliderParticle physicsJet quenchingNuclear physicsCharm (quantum number)HadronColliderProduction (economics)RapidityQuark–gluon plasma
DOInot available

Abstract

fetched live from OpenAlex

Effects of strong longitudinal colour electric fields (SCF), shadowing, and quenching on the open prompt charm mesons (D 0 , D +, D ∗ +, D s +) production in central Pb + Pb collisions at √ sNN = 2.76 TeV are investigated within the framework of the HIJING/BB v2.0 model. We compute the ¯ nuclear modification factor R D PbPb, and show that the above nuclear effects constitute important dynamical mechanisms in the description of experimental data. The strength of colour fields (as characterized by the string tension κ), partonic energy loss and jet quenching process lead to a suppression factor consistent with recent published data. Predictions for future beauty mesons measurements have been included. Ratios of strange to non-strange prompt charm mesons in central Pb + Pb and minimum bias (MB) p + p collisions at 2.76 TeV are also discussed. Minimum bias p + p collisions which constitute theoretical baseline in our calculations are studied at the centre of mass energies √ s = 2.76 TeV and 7 TeV.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.003
Open science0.0050.005
Research integrity0.0000.001
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 head0.021
GPT teacher head0.277
Teacher spread0.256 · 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.

Study designBench or experimental
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

Citations7
Published2014
Admission routes2
Has abstractyes

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