CHEMICAL ABUNDANCES IN A SAMPLE OF RED GIANTS IN THE OPEN CLUSTER NGC 2420 FROM APOGEE
Bibliographic record
Abstract
ABSTRACT NGC 2420 is a ∼2 Gyr old well-populated open cluster that lies about 2 kpc beyond the solar circle, in the general direction of the Galactic anti-center. Most previous abundance studies have found this cluster to be mildly metal-poor, but with a large scatter in the obtained metallicities. Detailed chemical abundance distributions are derived for 12 red-giant members of NGC 2420 via a manual abundance analysis of high-resolution (R = 22,500) near-infrared (λ1.5–1.7 μm) spectra obtained from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey. The sample analyzed contains six stars that are identified as members of the first-ascent red giant branch (RGB), as well as six members of the red clump (RC). We find small scatter in the star-to-star abundances in NGC 2420, with a mean cluster abundance of [Fe/H] = −0.16 ± 0.04 for the 12 red giants. The internal abundance dispersion for all elements (C, N, O, Na, Mg, Al, Si, K, Ca, Ti, V, Cr, Mn, Co and Ni) is also very small (∼0.03–0.06 dex), indicating a uniform cluster abundance distribution within the uncertainties. NGC 2420 is one of the clusters used to calibrate the APOGEE Stellar Parameter and Chemical Abundance Pipeline (ASPCAP). The results from this manual analysis compare well with ASPCAP abundances for most of the elements studied, although for Na, Al, and V there are more significant offsets. No evidence of extra-mixing at the RGB luminosity bump is found in the 12C and 14N abundances from the pre-luminosity-bump RGB stars in comparison to the post-He core-flash RC stars.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 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".