Atmospheric parameters and chemical abundances of young stars with APOGEE – I. Orion star-forming region
Bibliographic record
Abstract
ABSTRACT We derive atmospheric parameters and chemical abundances in young G-, K-, and M-type stars (temperatures between 6500 and 3100 K) using infrared APOGEE-2 spectra. Atmospheric parameters were determined for 548 young stars in the Orion complex (Orion A, B, OB1, and $\lambda$ Ori) using the tonalli code. For 340 slow rotators ($v\sin i$ $\le$ 30 km s$^{-1}$), we derived C, Mg, Si, K, Ti, and Fe abundances using 19 atomic lines, MARCS model atmospheres, and bacchus. To mitigate the impact of circumstellar material, we excluded stars with infrared excess identified via 2MASS and WISE photometry. We find subsolar [X/H] abundance ratios, consistent across elements and among all four groups, suggesting a chemically homogeneous Orion complex. We computed [$\alpha$/Fe] from [Mg/Fe], [Si/Fe], and [Ti/Fe], obtaining a median of $-0.14 \pm 0.04$, about 0.10 dex lower than the value for nearby main-sequence stars ($-0.04 \pm 0.04$) at similar [Fe/H]. This result aligns with predictions from Galactic chemical evolution models. Furthermore, the median [C/H] abundance we derived for Orion agrees with previous estimations based on the analysis of the ionized gas of the Orion nebula. This work sets the stage for extending the analysis to stars with circumstellar material and higher rotational velocities, which will not only improve our understanding of Orion, but also provide critical insight into the formation and evolution of young stars, as well as the chemical evolution of the Milky Way.
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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 | 0.001 | 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".