NLTE Stellar Population Synthesis of Globular Clusters Using Synthetic Integrated Light Spectra. II. Expanded Photometry and Sensitivity of Near-IR Spectral Features to Cluster Age and Metallicity
Bibliographic record
Abstract
Abstract We present an expanded investigation of the library of globular cluster (GC) synthetic integrated light (IL) spectra of Young & Short, focusing on the impact of non-local thermodynamic equilibrium (NLTE) modeling effects on cluster parameters derived from photometric colors and sensitivity of near-IR spectral features to cluster age and metallicity. Johnson–Cousins–Bessel UBVIJK photometric colors are produced for 910 synthetic IL spectra with two degrees of α enhancement, in both NLTE and local thermodynamic equilibrium (LTE). These color values are used to investigate the GC age–metallicity degeneracy and compare NLTE and LTE derived [M/H] values for NGC 104, NGC 5139, and NGC 6205. For a given age, derived [M/H] values are shown to increase by up to 0.05 dex when modeled in NLTE. A total of 86 spectral lines in the range λ = 12000–22000 Å, representing 14 different atomic species, were identified as sensitive to either cluster age or metallicity, 12 of which were identified as sensitive to both. Equivalent widths of the lines are measured in NLTE and LTE spectra, with NLTE effects changing the widths by up to <?CDATA ${}_{-0.15}^{+0.25}$?> Å depending on the atomic species.
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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".