METAL-POOR LITHIUM-RICH GIANTS IN THE RADIAL VELOCITY EXPERIMENT SURVEY
Bibliographic record
Abstract
We report the discovery of eight lithium-rich field giants found in a high-resolution spectroscopic sample of over 700 metal-poor stars ([Fe/H] < -0.5) selected from the Radial Velocity Experiment survey. The majority of the Li-rich giants in our sample are very metal-poor ([Fe/H] ≲ -1.9), and have a Li abundance (in the form of 7 Li), A (Li) = log ( n (Li)/ n (H)) + 12, between 2.30 and 3.63, well above the typical upper red giant branch (RGB) limit, A (Li) < 0.5, while two stars, with A (Li) ∼ 1.7–1.8, show similar lithium abundances to normal giants at the same gravity. We further included two metal-poor, Li-rich globular cluster giants in our sample, namely the previously discovered M3-IV101 and newly discovered (in this work) M68-A96. This comprises the largest sample of metal-poor Li-rich giants to date. We performed a detailed abundance analysis of all stars, finding that the majority of our sample stars have elemental abundances similar to that of Li-normal halo giants. Although the evolutionary phase of each Li-rich giant cannot be definitively determined, the Li-rich phase is likely connected to extra mixing at the RGB bump or early asymptotic giant branch that triggers cool bottom processing in which the bottom of the outer convective envelope is connected to the H-burning shell in the star. The surface of a star becomes Li-enhanced as 7 Be (which burns to 7 Li) is transported to the stellar surface via the Cameron–Fowler mechanism. We discuss and discriminate among several models for the extra mixing that can cause Li production, given the detailed abundances of the Li-rich giants in our sample.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".