BARIUM ISOTOPIC COMPOSITION OF MAINSTREAM SILICON CARBIDES FROM MURCHISON: CONSTRAINTS FOR<i>s</i>-PROCESS NUCLEOSYNTHESIS IN ASYMPTOTIC GIANT BRANCH STARS
Bibliographic record
Abstract
We present barium, carbon, and silicon isotopic compositions of 38 acid-cleaned presolar SiC grains from Murchison.Comparison with previous data shows that acid washing is highly effective in removing barium contamination.Strong depletions in δ( 138 Ba/ 136 Ba) values are found, down to -400‰, which can only be modeled with a flatter 13 C profile within the 13 C pocket than is normally used.The dependence of δ( 138 Ba/ 136 Ba) predictions on the distribution of 13 C within the pocket in asymptotic giant branch (AGB) models allows us to probe the 13 C profile within the 13 C pocket and the pocket mass in AGB stars.In addition, we provide constraints on the 22 Ne(α, n) 25 Mg rate in the stellar temperature regime relevant to AGB stars, based on δ( 134 Ba/ 136 Ba) values of mainstream grains.We found two nominally mainstream grains with strongly negative δ( 134 Ba/ 136 Ba) values that cannot be explained by any of the current AGB model calculations.Instead, such negative values are consistent with the intermediate neutron capture process (i process), which is activated by the very late thermal pulse during the post-AGB phase and characterized by a neutron density much higher than the s process.These two grains may have condensed around post-AGB stars.Finally, we report abundances of two p-process isotopes, 130 Ba and 132 Ba, in single SiC grains.These isotopes are destroyed in the s process in AGB stars.By comparing their abundances with respect to that of 135 Ba, we conclude that there is no measurable decay of 135 Cs (t 1/2 = 2.3 Ma) to 135 Ba in individual SiC grains, indicating condensation of barium, but not cesium into SiC grains before 135 Cs decayed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".