Evidence for Radiogenic Sulfur-32 in Type AB Presolar Silicon Carbide Grains?
Bibliographic record
Abstract
We report C, Si, and S isotope measurements on 34 presolar silicon carbide grains of Type AB, characterized by 12C/13C < 10. Nitrogen, Mg-Al-, and Ca-Ti-isotopic compositions were measured on a subset of these grains. Three grains show large 32S excesses, a signature that has been previously observed for grains from supernovae (SNe). Enrichments in 32S may be due to contributions from the Si/S zone and the result of S molecule chemistry in still unmixed SN ejecta or due to incorporation of radioactive 32Si from C-rich explosive He shell ejecta. However, a SN origin remains unlikely for the three AB grains considered here, because of missing evidence for 44Ti, relatively low 26Al/27Al ratios (a few times 10-3), and radiogenic 32S along with low 12C/13C ratios. Instead, we show that born-again asymptotic giant branch (AGB) stars that have undergone a very-late thermal pulse (VLTP), known to have low 12C/13C ratios and enhanced abundances of the light s-process elements, can produce 32Si, which makes such stars attractive sources for AB grains with 32S excesses. This lends support to the proposal that at least some AB grains originate from born-again AGB stars, although uncertainties in the born-again AGB star models and possible variations of initial S-isotopic compositions in the parent stars of AB grains make it difficult to draw a definitive conclusion.
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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 | 0.001 | 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".