Bibliographic record
Abstract
Context.Atomic diffusion is believed to cause the abundance anomalies observed in AmFm stars. However, the detailed process has still not been well-established. For instance, two possible scenarios for the diffusion theory are presently envisaged. They differ mainly by the depth from which the abundance anomalies emanate. The first scenario predicts that the abundances are modified in the superficial regions of the star, just below the hydrogen convection zone. The second scenario predicts that a much deeper extension of the mixing zone exists due to the convection caused by Fe accumulation in regions below the hydrogen convection zone. Aims.We calculate much more accurate radiative accelerations of Sc than previously, to better understand the observed abundance anomalies of this element. We believe that it is a key element to use as a diagnostic tool for understanding AmFm stars. Methods.The method employed to obtain these radiative accelerations is based on an interpolation from the parameters of the so-called SVP parametric method. Results.The radiative accelerations, shown here in a typical Am stellar model, are discussed in light of the observed anomalies of Ca and Sc. Our results suggest that the deeper mixing scenario is not entirely satisfactory: the mixing zone should be deeper than what is predicted by recent models to account for observed Sc underabundances. Our results seem more compatible with the scenario where the abundances anomalies are created in the superficial regions. However, only detailed evolutionary modelling with mass loss and diffusion of all important species, including Ca and Sc, with accurate radiative accelerations, will be able to give more insight into where the source of these anomalies occur in AmFm stars.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".