The Victoria‐Regina Stellar Models: Evolutionary Tracks and Isochrones for a Wide Range in Mass and Metallicity that Allow for Empirically Constrained Amounts of Convective Core Overshooting
Bibliographic record
Abstract
Seventy-two grids of stellar evolutionary tracks, along with the means to generate isochrones and luminosity/color functions from them, are presented in this investigation. Sixty of them extend (and encompass) the sets of models reported by VandenBerg et al. for 17 [Fe/H] values from -2.31 to -0.30 and α-element abundances corresponding to [α/Fe] = 0.0, 0.3, and 0.6 (at each iron abundance) to the solar metallicity and to sufficiently high masses (up to ~2.2 M ☉ ) that isochrones may be computed for ages as low as 1 Gyr. The remaining grids contain tracks for masses from 0.4 to 4.0 M ☉ and 12 [Fe/H] values between -0.60 and +0.49 (assuming solar metal-to-hydrogen number abundance ratios): in this case, isochrones may be calculated down to ~0.2 Gyr. The extent of convective core overshooting has been modeled using a parameterized version of the Roxburgh criterion, in which the value of the free parameter at a given mass and its dependence on mass have been determined from analyses of binary star data and the observed color-magnitude diagrams for several open clusters. Because the calculations reported herein satisfy many empirical constraints, they should provide useful probes into the properties of both simple and complex stellar populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".