Measurement of the nuclear modification factor for muons from charm and bottom hadrons in Pb+Pb collisions at 5.02 TeV with the ATLAS detector
Bibliographic record
Abstract
CERN-LHC. Heavy flavour hadron production provides information about the transport properties and the microscopic structure of the quark-gluon plasma created in ultra-relativistic heavy-ion collisions. A measurement of the production of muons from the semi-leptonic decays of charm and bottom hadrons in Pb+Pb and pp collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV with the ATLAS detector at the Large Hadron Collider is presented. The Pb+Pb data were collected in 2015 and 2018 with sampled integrated luminosities of 208 mub^-1 and 38 mub^-1, respectively, and pp data with a sampled integrated luminosity of 1.17 pb^-1 were collected in 2017. The differential muons yield in Pb+Pb and pp cross section are measured in the transverse momentum range from 4 GeV to 30 GeV and pseudorapidity interval up to 2. Muons from heavy flavour semi-leptonic decays are separated from the light flavour hadronic background using the momentum imbalance between the inner detector and the muon spectrometer measurements, and muons coming from charm and bottom decays are further separated via the muon track transverse impact parameter. The nuclear modification factor for the charm and bottom muons is presented as a function of the muon transverse momentum in intervals of Pb+Pb collision centrality. The measured nuclear modification factors quantify significant suppression of the yields for muons coming from the decays of charm and bottom hadron, with stronger effects for muons coming from charm hadron decays.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".