Timescale for equilibration of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>N</mml:mi><mml:mo>/</mml:mo><mml:mi>Z</mml:mi></mml:mrow></mml:math>gradients in dinuclear systems
Bibliographic record
Abstract
Equilibration of $N/Z$ in binary breakup of an excited and transiently deformed projectile-like fragment (PLF${}^{*}$), produced in peripheral collisions of ${}^{64}\mathrm{Zn}+{}^{27}$Al, ${}^{64}$Zn, ${}^{209}$Bi at $E/A=45$ MeV, is examined. The composition of emitted light fragments ($3\ensuremath{\le}Z\ensuremath{\le}6$) changes with the decay angle of the PLF${}^{*}$. The most neutron-rich fragments observed are associated with a small rotation angle. A clear target dependence is observed with the largest initial $N/Z$ correlated with the heavy, neutron-rich target. Using the rotation angle as a clock, we deduce that $N/Z$ equilibration persists for times as long as 3--4 zs ($1\phantom{\rule{4pt}{0ex}}\mathrm{zs}=1\ifmmode\times\else\texttimes\fi{}\phantom{\rule{0.16em}{0ex}}{10}^{\ensuremath{-}21}$ s $=300$ fm$/c$). The rate of $N/Z$ equilibration is found to depend on the initial neutron gradient within the PLF${}^{*}$.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".