On the Use of Blanketed Atmospheres as Boundary Conditions for Stellar Evolutionary Models
Bibliographic record
Abstract
Stellar models have been computed for stars having [ Fe/H ] = 0.0 (assuming both the Grevesse & Sauval and Asplund et al. heavy-element mixtures) and –2.0 to determine the effects on the predicted T eff scale of using boundary conditions derived from the latest MARCS model atmospheres. The latter were fitted in a fully consistent way to the interior models at the photosphere and at τ = 100: the resultant evolutionary sequences on the H-R diagram were found to be nearly independent of the chosen fitting point. Tracks were also computed in which the pressure at T = T eff was obtained by integrating the hydrostatic equation together with either the classical gray T (τ , T eff ) relation or that derived by Krishna Swamy from an empirical solar atmosphere. Due to the effects of differences in the solar-calibrated values of the mixing-length parameter, α MLT , very similar tracks were obtained for the different treatments of the atmosphere, except at solar abundances, where the models based on the Krishna Swamy T (τ , T eff ) relationship predicted ~150 K hotter giant branches than the others, in good agreement with the inferred temperatures of giants in the open cluster M67 from recent (V − K) - T eff relations. Tracks that used new ``scaled solar, differentially corrected'' MARCS atmospheres were found to agree well with those that employed the Krishna Swamy T (τ , T eff ) relationship, independently of the assumed metal abundance. (Gray atmospheres are quite different from MARCS models.) Fits of isochrones for [ Fe/H ] = − 2.0 to the CMD of the globular cluster M68, as well as the possibility that α MLT varies with stellar parameters, are also discussed.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".