On the asymptotic giant branch star origin of peculiar spinel grain OC2
Bibliographic record
Abstract
Context. Microscopic presolar grains extracted from primitive meteorites have extremely anomalous isotopic compositions revealing the stellar origin of these grains. Multiple elements in single presolar grains can be analysed with sensitive mass spectrometers, providing precise sets of isotopic compositions to be matched by theoretical models of stellar evolution and nucleosynthesis. Aims. The composition of presolar spinel grain OC2 is different from that of all other presolar spinel grains. In particular, large excesses of the heavy Mg isotopes are present and thus an origin from an intermediate-mass (IM) asymptotic giant branch (AGB) star was previously proposed for this grain. We discuss the O, Mg, Al, Cr and Fe isotopic compositions of presolar spinel grain OC2 and compare them to theoretical predictions. Methods. We use detailed models of the evolution and nucleosynthesis of AGB stars of different masses and metallicities to compare to the composition of grain OC2. We analyse the uncertainties related to nuclear reaction rates and also discuss stellar model uncertainties. Results. We show that the isotopic composition of O, Mg and Al in OC2 could be the signature of an AGB star of IM and metallicity close to solar experiencing hot bottom burning, or of an AGB star of low mass (LM) and low metallicity (similar or equal to 0.004) suffering very efficient cool bottom processing. Large measurement uncertainty in the Fe isotopic composition prevents us from discriminating which model better represents the parent star of OC2. However, the Cr isotopic composition of the grain favors an origin in an IM-AGB star of metallicity close to solar. Conclusions. Our IM-AGB models produce a self-consistent solution to match the composition of OC2 within the uncertainties related to reaction rates. Within this solution we predict that the O-16(p, gamma)F-17 and the O-17(p, alpha)N-14 reaction rates should be close to their lower and upper limits, respectively. By finding more g
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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 | 0.001 | 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".