McGill/00-21 From Crêpes to Pancakes in the MV Model 1
Bibliographic record
Abstract
Abstract. The McLerran-Venugopalan model provides a framework which allows one to compute the gluon distribution function of a very large nucleus from the equations of QCD, provided that the longitudinal momentum fraction, xF, is sufficiently small. The source of color charge for this computation may be thought of as a crêpe moving along the z axis at the speed of light. We refine the MV model by allowing for the presence of non-trivial longitudinal correlations between the color charges that comprise the nucleons. We find that a consistent treatment forces us to consider a pancake-like source which moves at slightly less than the speed of light. Our calculation allows us to consider larger values of x than were allowed in the original MV model. F Several years ago, McLerran and Venugopalan realized that for large enough nuclei at small enough values of the longitudinal momentum fraction x F, it ought to be possible to compute the gluon distribution function using QCD [1]. Based on this observation, the framework known as the McLerran-Venugopalan model
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".