The Gaia-ESO Survey: evidence of atomic diffusion in M67?
Bibliographic record
Abstract
Investigating the chemical homogeneity of stars born from the same molecular cloud at virtually the same time is very important for our understanding of the chemical enrichment of the interstellar medium and with it the chemical evolution of the Galaxy.One major cause of inhomogeneities in the abundances of open clusters is stellar evolution of the cluster members.In this work, we investigate variations in the surface chemical composition of member stars of the old open cluster M67 as a possible consequence of atomic diffusion effects taking place during the main-sequence phase.The abundances used are obtained from high-resolution UVES/FLAMES spectra within the framework of the Gaia-ESO Survey.We find that the surface abundances of stars on the main sequence decrease with increasing mass reaching a minimum at the turnoff.After deepening of the convective envelope in sub-giant branch stars, the initial surface abundances are restored.We found the measured abundances to be consistent with the predictions of stellar evolutionary models for a cluster with the age and metallicity of M67.Our findings indicate that atomic diffusion poses a non-negligible constraint on the achievable precision of chemical tagging methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".