Precision Mass Measurements Reveal Low Neutron Pairing in Tin beyond <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:mn>82</mml:mn> </mml:mrow> </mml:math> and Its Impact on Stellar Nucleosynthesis
Bibliographic record
Abstract
We present a study on neutron-rich tin (Z=50) isotopes beyond the doubly closed shell of N=82 through high-precision mass measurements, including the first-ever measurements of the masses of ^{136}Sn, ^{137}Sn, and ^{138}Sn isotopes. These measurements enhance our understanding of the nuclear structure and astrophysical nucleosynthesis in this previously unexplored region. The new mass data are used for evaluation of the final abundances of mass numbers A=135 and 137 in r-process network calculations. Our findings reveal a notable change in the empirical pairing gap for tin isotopes beyond the N=82 closed shell and a shift in the two-neutron-separation energy slope compared to heavier elements above the shell closure. A new set of ab initio calculations effectively describes these observed trends.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".