Models for metal-poor stars with different initial abundances of C, N, O, Mg, and Si − III. Grids of isochrones for −2.5 ≤ [Fe/H] ≤ −0.5 and helium abundances <i>Y</i> = 0.25 and 0.29 at each metallicity
Bibliographic record
Abstract
ABSTRACT Stellar evolutionary tracks for $0.12 \le {\cal M}/{\cal M_{\odot }}\le 1.0$ have been computed for each of several variations in the abundances of C, N, and O, assuming mass-fraction helium abundances Y = 0.25 and 0.29, and 11 metallicities in the range −2.5 ≤ [Fe/H] ≤ −0.5, in 0.2-dex increments. Such computations are provided for mixtures with [O/Fe] between +0.4 and +0.8, for different C:N:O ratios at a fixed value of [CNO/Fe] and for enhanced C. Computer codes are provided to interpolate within these grids to produce isochrones for ages ${\gtrsim}7$ Gyr and to generate magnitudes and colours for many broad-band filters using bolometric corrections based on MARCS model atmospheres and synthetic spectra. The models are compared with (i) similar computations produced by other workers, (ii) observed UV, optical, and IR colour-magnitude diagrams (CMDs), (iii) the effective temperatures, (V − IC)0 and (V − KS)0 colours of Pop. II stars in the solar neighbourhood, and (iv) empirical data for the absolute magnitude of the tip of the red-giant branch (TRGB). The isochrones are especially successful in reproducing the observed morphologies of optical CMDs and in satisfying the TRGB constraints. They also fare quite well in explaining the IR colours of low-mass stars in globular clusters, indicating that they have [O/Fe] ≈ +0.6, though some challenges remain.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".