Ba Enrichment in Gaia MS+WD Binaries: Tracing s-process Element Production
Bibliographic record
Abstract
Abstract A large population of intermediate-separation binaries, consisting of a main-sequence (MS) star and a white dwarf (WD), recently emerged from Gaia’s third data release (DR3), posing challenges to current models of binary evolution. Here we examine the s -process element abundances in these systems using data from GALAH DR3. Following refined sample analysis with parameter estimates based on GALAH spectra, we find a distinct domain where enhanced s -process elemental abundances depend on both the WD mass and metallicity, consistent with parameter spaces identified in previous asymptotic giant branch (AGB) nucleosynthesis studies having higher s -process yields. Notably, these enhanced abundances show no correlation with the systems’ orbital parameters, supporting a history of accretion in intermediate-separation MS+WD systems. Consequently, our results form direct observational evidence of a connection between AGB masses and s -process yields. We conclude by showing that the GALAH DR3 survey includes numerous Ba dwarf stars, within and beyond the mass range covered in our current sample, which can further elucidate s -process element distributions in MS+WD binaries.
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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 | 0.001 |
| 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".