The complex magnetic field topology of the cool Ap star 49 Cam
Bibliographic record
Abstract
49 Cam is a cool magnetic chemically peculiar star that has been noted for showing strong, complex Zeeman linear polarization signatures. This paper describes magnetic and chemical surface maps obtained for 49 Cam using the Invers10 magnetic Doppler imaging code and high-resolution spectropolarimetric data in all four Stokes parameters collected with the ESPaDOnS and Narval spectropolarimeters at the Canada–France–Hawaii Telescope and Pic du Midi Observatory. The reconstructed magnetic field maps of 49 Cam show a relatively complex structure. Describing the magnetic field topology in terms of spherical harmonics, we find significant contributions of modes up to ℓ = 3, including toroidal components. Observations cannot be reproduced using a simple low-order multipolar magnetic field structure. 49 Cam exhibits a level of field complexity that has not been seen in magnetic maps of other cool Ap stars. Hence, we concluded that relatively complex magnetic fields are observed in Ap stars at both low and high effective temperatures. In addition to mapping the magnetic field, we also derive surface abundance distributions of nine chemical elements, including Ca, Sc, Ti, Cr, Fe, Ce, Pr, Nd and Eu. Comparing these abundance maps with the reconstructed magnetic field geometry, we find no clear relationship of the abundance distributions with the magnetic field for some elements. However, for other elements some distinct patterns are found. We discuss these results in the context of other recent magnetic mapping studies and theoretical predictions of radiative diffusion.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".