Tracking saddle-to-scission dynamics using<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>in projectile breakup reactions
Bibliographic record
Abstract
Fragments produced in binary splits of an excited projectile-like fragment (PLF${}^{*}$) formed in the reactions ${}^{124}$Xe $+$ ${}^{112,124}$Sn at an incident energy of 50 MeV/$A$ are examined. The dependence of the isotopic composition of light fragments ($4\ensuremath{\leqslant}{Z}_{L}\ensuremath{\leqslant}8$) on rotation angle allows one to explore changes in $N/Z$ on the time scale of the rotational period of the PLF${}^{*}$. Changes in the $N/Z$ of the fragments persist for times as long as 2--3 zs (600--900 fm/$c$). The two-component nature of the time dependence of $\ensuremath{\langle}N\ensuremath{\rangle}/Z$ for ${Z}_{L}=4$ and the $Z$ dependence are related to differences in the initial configurations and subsequent decay of the PLF${}^{*}$.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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".