Main Sequence Evolution, Abundance Anomalies and Particle Transport
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The availability of large atomic data bases has made it possible to calculate stellar evolution models taking into detailed account the abundance variations of all important contributors to opacity. In a first step, in addition to nuclear reactions, the atomic diffusion, radiative accelerations and opacity are continuously calculated during evolution taking the abundance changes of 28 species into account. This leads to the first self consistent main sequence stellar evolution models. In A and F stars ( M ≥ 1.5 M ʘ ) an iron peak convection zone is shown to appear at a temperature of 200000 K. The calculated surface abundance anomalies, that follow without any arbitrary parameter, are very similar to those observed in AmFm stars in open clusters except that they are larger by a factor of about 3. The second step, is then to introduce a competing hydrodynamical process. To reduce the calculated anomalies to the observed ones, turbulence has been introduced. It is found that the mixed zone must be about 5 times deeper than the iron convection zone. Detailed comparisons to a few AmFm stars have been carried out. The determination of the abundance anomalies of a large number of atomic species (20 to 30 are probably accessible) makes it possible to constrain stellar hydrodynamics. In clusters, the original abundances and age may be known and the accurate determination of surface abundances may constrain turbulence, mass loss and differential rotation when the required atomic data bases are available and used for the modeling of particle transport in stellar evolution.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it