Cu I resonance lines in turn-off stars of NGC 6752 and NGC 6397. Effects of granulation from CO5BOLD models
Bibliographic record
Abstract
Context. Copper is an element whose interesting evolution with metallicity is not fully understood. Observations of copper abundances rely on a very limited number of lines, the strongest are the Cu I lines of Mult. 1 at 324.7 nm and 327.3 nm which can be measured even at extremely low metallicities. Aims. We investigate the quality of these lines as abundance indicators. Method. We measure these lines in two turn-off (TO) stars in the Globular Cluster NGC 6752 and two TO stars in the Globular Cluster NGC 6397 and derive abundances with 3D hydrodynamical model atmospheres computed with the CO5BOLD code. These abundances are compared to the Cu abundances measured in giant stars of the same clusters, using the lines of Mult. 2 at 510.5 nm and 578.2 nm. Results. The abundances derived from the lines of Mult. 1 in TO stars differ from the abundances of giants of the same clusters. This is true both using CO5BOLD models and using traditional 1D model atmospheres. The LTE 3D corrections for TO stars are large, while they are small for giant stars. Conclusions. The Cu I resonance lines of Mult. 1 are not reliable abundance indicators. It is likely that departures from LTE should be taken into account to properly describe these lines, although it is not clear if these alone can account for the observations. An investigation of these departures is indeed encouraged for both dwarfs and giants. Our recommendation to those interested in the study of the evolution of copper abundances is to rely on the measurements in giants, based on the lines of Mult. 2. We caution, however, that NLTE studies may imply a revision in all the Cu abundances, both in dwarfs and giants.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".