A statistical model analysis of yields and fluctuations in 200 GeV Au-Au\n collisions
Bibliographic record
Abstract
We show that the simultaneous measurement of yields and fluctuations is\ncapable of falsifying and constraining the statistical hadronization model. We\nshow how such a measurement can test for chemical non-equilibrium, and\ndistinguish between a high temperature chemically equilibrated freeze-out from\na supercooled freeze-out with an over-saturated phase space. We perform a fit,\nand show that both yields and fluctuations measured at RHIC 200 GeV can be\naccounted for within the second scenario, with both the light and strange quark\nphase space saturated significantly above detailed balance. We point to the\nsimultaneous fit of the $K/\\pi$ fluctuation and the $K^*/K^-$ ratio as evidence\nthat the effect of hadronic re-interactions after freeze-out is small.\n
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".