Precision mass measurements of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mmultiscripts> <mml:mi>Sr</mml:mi> <mml:mprescripts/> <mml:none/> <mml:mrow> <mml:mn>74</mml:mn> <mml:mo>−</mml:mo> <mml:mn>76</mml:mn> </mml:mrow> </mml:mmultiscripts> </mml:math> using the multiple reflection time-of-flight mass spectrometer at TITAN
Bibliographic record
Abstract
We report precision mass measurements of $^{74\ensuremath{-}76}\mathrm{Sr}$ performed with the TITAN multiple-reflection time-of-flight mass spectrometer. This marks a first-time mass measurement of $^{74}\mathrm{Sr}$ and gives increased mass precision to both $^{75}\mathrm{Sr}$ and $^{76}\mathrm{Sr}$, which were previously measured using storage ring and Penning trap methods, respectively. This completes the $A=74$, $T=1$ isospin triplet and gives increased precision to the $A=75$, $T=1/2$ isospin doublet, which are both the heaviest experimentally evaluated triplets and doublets to date. The new data allow us to evaluate coefficients of the isobaric multiplet mass equation for the first time at $A=74$ and with increased precision at $A=75$. With increased precision of $^{75}\mathrm{Sr}$, we confirm the recent measurement reported by CSRe that was used to remove a staggering anomaly in the doublets. New ab initio valence-space in-medium similarity renormalization group calculations of the $T=1$ triplet are presented at $A=74$. We also investigate the impact of the new mass data on the reaction flow of the rapid proton capture process in type I x-ray bursts using a single-zone model.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".