MétaCan
Menu
Back to cohort
Record W3198136273 · doi:10.22323/1.387.0039

Event-plane decorrelation of photons produced in the early stage of heavy-ion collisions

2021· article· en· W3198136273 on OpenAlexafffund
Jean-François Paquet, Charles Gale, Bjoern Schenke, Chun Shen

Bibliographic record

VenueProceedings of 10th International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear Collisions — PoS(HardProbes2020) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaNational Energy Research Scientific Computing CenterU.S. Department of EnergyOffice of ScienceNational Science Foundation
KeywordsDecorrelationPhysicsPhotonHeavy ionAnisotropyHadronEvent (particle physics)Nuclear physicsPlane (geometry)Momentum (technical analysis)IonAstrophysicsQuantum mechanicsComputer science

Abstract

fetched live from OpenAlex

We study photon production in the early stage of heavy-ion collisions using a multistage model combining IP-Glasma, \kompost{} and relativistic hydrodynamics. We discuss the small momentum anisotropy of these photons, highlighting the role of the photon-hadron event-plane decorrelation. We comment that this singular characteristic of early photons could be used to provide dynamical information on the complex pre-hydrodynamics phase of heavy-ion collisions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.259
Teacher spread0.244 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of 10th International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear Collisions — PoS(HardProbes2020)Same topicHigh-Energy Particle Collisions ResearchFrench-language works237,207