Model-independent tracking of criticality signals in nuclear multifragmentation data
Bibliographic record
Abstract
We look for signals of criticality in multifragment production in heavy-ion collisions using model-independent universal fluctuations theory. The phenomenon is studied as a function of system size, bombarding energy, and impact parameter over a wide range of INDRA data. For very central collisions $(b/{b}_{\mathrm{max}}<0.1)$ we find evidence that the largest fragment in each event, ${Z}_{\mathrm{max}}$, plays the role of an order parameter, defining two different regimes at low and high incident energy, respectively, according to the scaling properties of its fluctuations. Data for a wide range of system masses and incident energies collapse on to an approximately universal scaling function in each regime for the most central collisions. The forms of the scaling functions for the two regimes are established, and their dependence on the total mass and the bombarding energy is mapped out. Data suggest that these regimes are linked to the disappearance of heavy residues in central collisions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".