Charge correlations and isotopic distributions of projectile fragmentation events in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mmultiscripts><mml:mi mathvariant="normal">Xe</mml:mi><mml:mprescripts/><mml:none/><mml:mrow><mml:mn>124</mml:mn></mml:mrow></mml:mmultiscripts><mml:mrow><mml:mo>+</mml:mo></mml:mrow><mml:mmultiscripts><mml:mi mathvariant="normal">Sn</mml:mi><mml:mprescripts/><mml:none/><mml:mrow><mml:mn>112</mml:mn></mml:mrow></mml:mmultiscripts></mml:math>at<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>E</mml:mi><mml:mo>/</mml:mo><mml:mi>A</mml:mi><mml:mo>=</mml:mo><mml:mn>50</mml:mn></mml:mrow></mml:math>MeV
Bibliographic record
Abstract
Ternary breakup of an excited projectile-like fragment produced in mid-peripheral collisions of $^{124}\mathrm{Xe}$ projectiles with $^{112}\mathrm{Sn}$ nuclei at $E/A=50$ MeV is examined. Charge correlations reveal that symmetric breakups occur with significant probability. By selecting on the parallel velocity of the heaviest fragment we minimize the entrance channel dynamics. Calculations with the statistical decay code GEMINI failed to reproduce the experimental charge correlations for any suitable combination of excitation energy and spin considered. A statistical multifragmentation model (SMM) in which breakup of low-density nuclear matter is assumed was able to reproduce the observed charge correlations. The $\ensuremath{\langle}N\ensuremath{\rangle}/Z$ and isotope distributions of fragments were compared to the results of the SMM calculations. Describing the $\ensuremath{\langle}N\ensuremath{\rangle}/Z$ of heavy fragments ($Z>6$) within SMM suggests that a reduction of the symmetry energy parameter from $\ensuremath{\gamma}=25$ to $14$ MeV is necessary. We observe that the yield of neutron-rich isotopes of heavy fragments is particularly sensitive to the symmetry energy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.100 | 0.014 |
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".