PRODUCTION OF CARBON-RICH PRESOLAR GRAINS FROM MASSIVE STARS
Bibliographic record
Abstract
About a year after core-collapse supernova, dust starts to condense in the ejecta. In meteorites, a fraction of C-rich presolar grains (e.g., silicon carbide (SiC) grains of Type-X and low density graphites) are identified as relics of these events, according to the anomalous isotopic abundances. Several features of these abundances remain unexplained and challenge the understanding of core-collapse supernovae explosions and nucleosynthesis. We show, for the first time, that most of the measured C-rich grain abundances can be accounted for in the C-rich material from explosive He burning in core-collapse supernovae with high shock velocities and consequent high temperatures. The inefficiency of the 12 C(α, γ) 16 O reaction relative to the rest of the α-capture chain at T > 3.5 × 10 8 K causes the deepest He-shell material to be carbon-rich and silicon-rich, and depleted in oxygen. The isotopic ratio predictions in part of this material, defined here as the C/Si zone, are in agreement with the grain data. The high-temperature explosive conditions that our models reach at the bottom of the He shell can also be representative of the nucleosynthesis in hypernovae or in the high-temperature tail of a distribution of conditions in asymmetric supernovae. Finally, our predictions are consistent with the observation of large 44 Ca/ 40 Ca observed in the grains. This is due to the production of 44 Ti together with 40 Ca in the C/Si zone and/or to the strong depletion of 40 Ca by neutron captures.
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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 | 0.000 | 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".