Azimuthal anisotropies of charged particles with high transverse momentum in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Pb</mml:mi> <mml:mo>+</mml:mo> <mml:mi>Pb</mml:mi> </mml:mrow> </mml:math> collisions at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msqrt> <mml:msub> <mml:mi>s</mml:mi> <mml:mi>NN</mml:mi> </mml:msub> </mml:msqrt> <mml:mo>=</mml:mo> <mml:mn>5.02</mml:mn> </mml:mrow> </mml:math> TeV with the ATLAS detector
Bibliographic record
Abstract
A measurement is presented of elliptic ( v 2 ) and triangular ( v 3 ) azimuthal anisotropy coefficients for charged particles produced in Pb + Pb collisions at s NN = 5.02 TeV using a dataset corresponding to an integrated luminosity of 0.44 nb − 1 collected with the ATLAS detector at the LHC in 2018. The values of v 2 and v 3 are measured for charged particles over a wide range of transverse momentum ( p T ), 1–400 GeV , and Pb + Pb collision centrality, 0–60%, using the scalar-product and multiparticle cumulant methods. These methods are sensitive to event-by-event fluctuations and nonflow effects in the measurements of azimuthal anisotropies. Positive values of v 2 are observed up to a p T of approximately 100 GeV from both methods across all centrality intervals. Positive values of v 3 are observed up to approximately 25 GeV using both methods, though the application of the three-subevent technique to the multiparticle cumulant method leads to significant changes at the highest p T . At high p T ( p T ⪆ 10 GeV ), charged particles are dominantly from jet fragmentation. These jets, and hence the measurements presented here, are sensitive to the path-length dependence of parton energy loss in the quark-gluon plasma produced in Pb + Pb collisions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".