Models of metal-poor stars with different initial abundances of C, N, O, Mg, and Si – I. Bolometric corrections derived from new MARCS synthetic spectra and their implications for observed colour–magnitude diagrams
Bibliographic record
Abstract
ABSTRACT New, high-resolution MARCS synthetic spectra have been calculated for more than a dozen mixtures of the metals allowing, in turn, for variations in C:N:O, [CNO/Fe], and enhanced abundances of C, O, Mg, and Si. Bolometric corrections (BCs) for many of the broad-band filters currently in use have been generated from these spectra. Due to improved treatments of molecules that involve atoms of C, N, and O, the BCs for UV and blue passbands, in particular, differ substantially from those derived from previous MARCS models. These differences, and the effects on the BCs of varying the abundances of the metals, are shown in a number of instructive plots. Stellar evolutionary grids for −2.5 ≤ [Fe/H] ≤−0.5 have also been computed for the different mixtures. Isochrones based on these tracks are intercompared on the theoretical H–R diagram and on a few of the colour–magnitude diagrams that can be constructed from HST Wide Field Camera 3 (WFC3) F336W, F438W, F606W, F814W, F110W, and F160W observations. For the first application of these models, isochrones have been fitted to WFC3 photometry of the globular cluster NGC 6496 from the HST UV Legacy Survey, with very encouraging results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".