Characterization of nuclear breakup as a function of hard-scattering kinematics using dijets measured by ATLAS in $p$+Pb collisions
Bibliographic record
Abstract
This Letter analyzes the sensitivity of event geometry estimators to the initial-state kinematics of hard scattering in proton-lead collisions. This analysis uses dijets as a proxy for the parton-parton scattering configuration, correlating it with event geometry estimators, namely the energy deposited in the Zero-Degree Calorimeter and the transverse energy recorded in the Forward Calorimeter in the Pb-going direction. The analysis uses data recorded by the ATLAS detector at the Large Hadron Collider with a nucleon-nucleon center-of-mass energy of 8.16 TeV, corresponding to an integrated luminosity of 56 nb$^{-1}$. The jets are measured within the pseudorapidity interval $-$2.8 $<$$\eta$$<$ 4.5, where positive $\eta$ values correspond to the direction of the proton beam. Results are presented as a function of the Bjorken-$x$ of the parton originating from the proton, $x_{p}$. Both event geometry estimators are found to be dependent on $x_{p}$, with the energy deposited in the Zero-Degree Calorimeter about six times less sensitive to $x_{p}$ compared with the transverse energy deposited in the Forward Calorimeter.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".