Thermal Stability of Rotating Low‐Mass Subgiants and Red Giants
Bibliographic record
Abstract
A linear analysis of the thermal stability of rotating low-mass stars evolving from the zero-age main sequence (ZAMS) to the red giant branch (RGB) tip has been carried out. Two stellar models are considered: one for 1.2 M ☉ with solar metallicity ( Z = 0.0188), and the other for 0.8 M ☉ with Z = 0.0005. An instability in a thermonuclear burning shell on the RGB in the first of these cases could potentially be related to the phenomenon of Li-rich red giants, while a hydrogen shell instability in the second model may help to explain the observed chemical abundance anomalies in globular cluster red giants. A range of surface rotational velocities in MS stars has been considered, and we have assumed that, beginning at the ZAMS, the stars (including their convective envelopes) rotate differentially with depth. This assumption, which leads to significantly higher centrifugal accelerations in the H-burning shell than with the case of solid-body rotation on the MS, is expected to favour the development of thermal instabilities. However, all of our models for rotating low-mass stars—even those that had much higher rotation rates on the MS than those observed for F-, G-, and K-type dwarfs—were found to be thermally stable throughout their evolution from the ZAMS to the RGB tip. Only when helium burning was ignited to end the first ascent of the giant branch did we find a thermal instability (the helium flash).
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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".