Chemical peculiarities in magnetic and non-magnetic pre-main sequence A and B stars
Bibliographic record
Abstract
Abstract In A- and late B-type stars, strong magnetic fields are always associated with Ap and Bp chemical peculiarities. However, it is not clear at what point in a star's evolution those peculiarities develop. Strong magnetic fields have been observed in pre-main sequence A and B stars (Herbig Ae and Be stars), and these objects have been proposed to be the progenitors of Ap and Bp stars. However, the photospheric chemical abundances of these magnetic Herbig stars have not been studied carefully, and furthermore the chemical abundances of 'normal' non-magnetic Herbig stars remain poorly characterized. To investigate this issue, we have studied the photospheric compositions of 23 Herbig stars, four of which have confirmed magnetic fields. Surprisingly, we found that half the non-magnetic stars in our sample show λ Bootis chemical peculiarities to varying degrees. For the stars with detected magnetic fields, we find one chemically normal star, one star with λ Boo peculiarities, one star displaying weak Ap/Bp peculiarities, and one somewhat more evolved star with somewhat stronger Ap/Bp peculiarities. These results suggests that Ap/Bp peculiarities are preceded by magnetic fields, and that these peculiarities develop over the pre-main sequence lives of A and B stars. The incidence of λ Boo stars we find is much higher than that seen on the main sequence. We argue that a selective accretion model for the formation of λ Boo peculiarities is a natural explanation for this remarkably large incidence.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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 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".