<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>3</mml:mn><mml:mo>+</mml:mo></mml:mrow><mml:mn>1</mml:mn><mml:mtext>D</mml:mtext></mml:math> initialization and evolution of the glasma
Bibliographic record
Abstract
The ip-glasma initial condition has been highly successful in the phenomenology of ultrarelativistic heavy ion collisions. The assumption of boost invariance, however, while good for collision energies probed at the Large Hadron Collider, limits the use of ip-glasma to the transverse dynamics of heavy ion collision to near midrapidity. There is a wealth of physics to be explored and understood in the longitudinal dynamics of heavy ion collisions, and a full understanding of heavy ion collisions can only come from three-dimensional studies. In particular, long range rapidity correlations are seeded in the initial collision and provide additional information on the high energy nuclear wave functions that have thus far been inaccessible to the ip-glasma model. In this paper, we introduce a way to extend the ip-glasma model to $3+1$ dimensions while preserving its key features.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.403 | 0.245 |
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".