Femtoscopy with identified charged pions in proton-lead collisions at √sNN = 5.02 TeV with ATLAS
Bibliographic record
Abstract
Bose-Einstein correlations between identified charged pions are measured for p+Pb collisions at √ s NN = 5.02 TeV using data recorded by the ATLAS detector at the CERN Large Hadron Collider corresponding to a total integrated luminosity of 28 nb -1 .Pions are identified using ionization energy loss measured in the pixel detector.Two-particle correlation functions and the extracted source radii are presented as a function of collision centrality as well as the average transverse momentum (k T ) and rapidity (y ππ ) of the pair.Pairs are selected with a rapidity -2 < y ππ < 1 and with an average transverse momentum 0.1 < k T < 0.8 GeV.The effect of jet fragmentation on the two-particle correlation function is studied, and a method using opposite-charge pair data to constrain its contributions to the measured correlations is described.The measured source sizes are substantially larger in more central collisions and are observed to decrease with increasing pair k T .A correlation of the radii with the local charged-particle density is demonstrated.The scaling of the extracted radii with the mean number of participating nucleons is also used to compare a selection of initial-geometry models.The cross term R ol is measured as a function of rapidity, and a nonzero value is observed with 5.1σ combined significance for -1 < y ππ < 1 in the most central events.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".