Bibliographic record
Abstract
Stellar evolution models have been calculated for stars of 1.7-2.5 M ☉ with both the Geneva-Toulouse and Montreal codes. In the Geneva-Toulouse code, the internal evolution of angular momentum is calculated self-consistently along with the transport of a few species. In the Montreal code, the transport of 24 species is treated in detail, taking into account radiative accelerations, thermal diffusion, and gravitational settling, along with the turbulent diffusion coefficients calculated in the Geneva-Toulouse code. It is verified that the two codes lead to very similar internal structure for a given mass. The calculated surface abundances are compared to abundance anomalies observed on AmFm stars. It is found that with approximately the same parameters as used for other types of stars, the Geneva-Toulouse code leads to turbulent transport coefficients that produce abundance anomalies consistent with the observed ones for HD 73045, HD 23610, and Sirius. Taking into account the effect of the anisotropy of turbulence on vertical transport plays an important role, although the level of anisotropy in stellar envelopes is very uncertain; this effect is usually neglected in calculations. The stabilizing effect of the mean molecular weight gradient can also be important. The current level of accuracy of observed abundances only permits to choose within a one-parameter family of models. To distinguish between turbulent models with different interior profiles, an accuracy of 0.03 dex is required of abundance determinations, a level of accuracy that is not currently achieved. It is also shown that taking into account the pre-main-sequence evolution of the rotation profile leads to an important reduction in the Ω dependence of turbulent transport for slow rotators.
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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 | 0.004 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".