Lithium evolution in the low-mass evolved stars with asteroseismology and LAMOST spectroscopy
Bibliographic record
Abstract
Lithium is an ancient element that was first produced by the Big Bang Nucleosynthesis (BBN) a few minutes after the birth of the Universe. Lithium is a sensitive tracer for a number of processes in a variety of astrophysical environments due to its multi-channels of production and fragility. These features also make lithium a complex element at the center of many unsolved problems. The behavior of lithium in the low-mass evolved stars is one such issue. It is known that such stars not only destroy but also produce lithium, while neither the destruction details nor the production mechanisms over different evolutionary phases are clear. In this paper, we summarize the recent results obtained from the studies combining large-scale spectroscopic surveys, asteroseismology, and traditional high-resolution spectroscopy. We present the detailed evolution behaviors from the red giant branch (RGB) to the red clump (RC) phase characterized by the core helium-burning in the stellar interior. We show the new signatures discovered from the recent studies for the lithium-enhanced giants and also discuss various observational and theoretical constraints on lithium production in red clump stars.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".