Measurement of jet $p_{\mathrm{T}}$ correlations in Pb+Pb and $pp$ collisions at $\sqrt{s_{\mathrm{NN}}}=$ 2.76 TeV with the ATLAS detector
Bibliographic record
Abstract
Measurements of dijet $p_T$ correlations in Pb+Pb and pp collisions at a nucleon–nucleon centre-of-mass energy of $\sqrt{{s}NN}$ = 2.76 TeV are presented. The measurements are performed with the ATLAS detector at the Large Hadron Collider using Pb + Pb and pp data samples corresponding to integrated luminosities of 0.14 nb$^{−1}$ and 4.0 pb$^{−1}$ , respectively. Jets are reconstructed using the anti-$k_t$ algorithm with radius parameter values R = 0.3 and R = 0.4 . A background subtraction procedure is applied to correct the jets for the large underlying event present in Pb+Pb collisions. The leading and sub-leading jet transverse momenta are denoted $p_{{T}_{1}}$ and $p_{{T}_{2}}$ . An unfolding procedure is applied to the two-dimensional ( $p_{{T}_{1}}, p_{{T}_{2}}$ ) distributions to account for experimental effects in the measurement of both jets. Distributions of (1/N)dN/$dx_J$ , where $x_J$ = $p_{{T}_{1}} / p_{{T}_{2}}$ , are presented as a function of $p_{{T}_{1}}$ and collision centrality. The distributions are found to be similar in peripheral Pb+Pb collisions and pp collisions, but highly modified in central Pb + Pb collisions. Similar features are present in both the R = 0.3 and R = 0.4 results, indicating that the effects of the underlying event are properly accounted for in the measurement. The results are qualitatively consistent with expectations from partonic energy loss models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".