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Record W2038398153 · doi:10.1142/s0218301307009087

PROSPECTS OF MEDIUM TOMOGRAPHY USING 2-, 3- AND 4-PARTICLE CORRELATIONS FOR A (SEMI)-HARD TRIGGER

2007· article· en· W2038398153 on OpenAlexaff
Thorsten Renk, Jörg Ruppert

Bibliographic record

VenueInternational Journal of Modern Physics E · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPartonPhysicsHadronMonte Carlo methodNuclear physicsProtonLarge Hadron ColliderNucleusSpectral lineYield (engineering)Particle (ecology)Energy (signal processing)Particle physics

Abstract

fetched live from OpenAlex

Hard partons propagating through hot and dense matter lose energy, leading to the observed depletion of hard hadron spectra in nucleus nucleus collision as compared to scaled proton proton collisions. This lost energy has to be redistributed in the medium due to the conservation of energy, which is manifest in the pT dependence of the angular correlation pattern of hadrons associate with a (semi-) hard trigger. While at low pT a splitting of a broad peak is observed, at high pT the structure shows vacuum width, albeit with reduced yield. This sugests a transfer of energy from hard partons to a collectively recoiling medium. We present a systematic study of these phenomena using a realistic medium evolution and a Monte-Carlo simulation of the experimental trigger and show what information about the medium can be derived from multiparticle correlations.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.336
Teacher spread0.304 · 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 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

Citations8
Published2007
Admission routes1
Has abstractyes

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Same venueInternational Journal of Modern Physics ESame topicHigh-Energy Particle Collisions ResearchFrench-language works237,207