High-resolution infrared spectroscopy of the dust-obscured metal-poor open cluster Trumpler 5
Bibliographic record
Abstract
Context. Open clusters are important tools to investigate the chemistry of the Galactic disk. Trumpler 5 is a moderately old, dust-obscured metal-poor open cluster. In this study, high-resolution near-infrared spectroscopic data of seven giant stars from the Trumpler 5 cluster were analyzed to derive chemical abundances for 20 elements and 12C/13C ratios. A color-magnitude diagram (CMD) analysis of BV and Gaia photometry has also been performed for a comprehensive study of the cluster. Aims. This work uses high-resolution near-infrared spectroscopy exclusively to derive atmospheric parameters and chemical abundances in the obscured open cluster Trumpler 5. Thanks to the methodology employed, some targets are studied for the first time. Additionally, it provides a detailed CMD analysis using photometric and spectroscopic data. Methods. We gathered high-resolution spectra for seven Trumpler 5 red giants in the near-infrared H and K wavelength domains, using the Immersion Grating INfrared Spectrometer (IGRINS). Five out of seven targets have been studied for the first time here with high-resolution spectroscopy. We introduced a method to initially estimate the stellar surface gravity (log g) by using calibrated equivalent widths of the Ti II line at 15 873 Å from a large sample. We performed standard spectroscopic analyses to refine the model atmospheric parameters of our targets and determined the chemical abundances primarily through spectrum synthesis. We also performed CMD analyses to extract differential reddening correction to compare cluster parameters both with and without corrections. Results. We derived stellar parameters for seven members of Trumpler 5 with our method and the results are consistent with both the literature and other methods. We also inferred elemental abundances for more than 20 species, along with the 12C/13C ratios. The elemental abundances are in good agreement with the literature values for similar targets. Through CMD analysis, we found the reddening value, E(B-V)≃0.76, and estimated the age of the cluster to be approximately 2.50 Gyr.
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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) | 0.000 | 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".