Lithium Depletion of Nearby Young Stellar Associations
Bibliographic record
Abstract
We estimate cluster ages from lithium depletion in five pre-main-sequence groups found within 100 pc of the Sun: the TW Hydrae association, η Chamaeleontis cluster, β Pictoris moving group, Tucanae-Horologium association, and AB Doradus moving group. We determine surface gravities, effective temperatures, and lithium abundances for over 900 spectra through least-squares fitting to model-atmosphere spectra. For each group, we compare the dependence of lithium abundance on temperature with isochrones from pre-main-sequence evolutionary tracks to obtain model-dependent ages. We find that the η Cha cluster and the TW Hydrae association are the youngest, with ages of 12 ± 6 Myr and 12 ± 8 Myr, respectively, followed by the β Pic moving group at 21 ± 9 Myr, the Tucanae-Horologium association at 27 ± 11 Myr, and the AB Dor moving group at an age of at least 45 Myr (whereby we can only set a lower limit, since the models—unlike real stars—do not show much lithium depletion beyond this age). Here the ordering is robust, but the precise ages depend on our choice of both atmospheric and evolutionary models. As a result, while our ages are consistent with estimates based on Hertzsprung-Russell isochrone fitting and dynamical expansion, they are not yet more precise. Our observations do show that with improved models, much stronger constraints should be feasible, as the intrinsic uncertainties, as measured from the scatter between measurements from different spectra of the same star, are very low: around 10 K in effective temperature, 0.05 dex in surface gravity, and 0.03 dex in lithium abundance.
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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".