Cartography of the magnetic fields and chemical spots of Ap stars
Bibliographic record
Abstract
Abstract We will introduce a project using Magnetic Doppler Imaging (MDI) to create assumption-free vector magnetic field maps and chemical surface structure maps of chemically peculiar A and B type (or Ap) stars. We are exploiting the latest generation of spectropolarimeters (NARVAL at the Pic du Midi observatory, and ESPaDOnS at the Canada-France-Hawaii telescope), to obtain high-resolution time series of Stokes IQUV spectra of a selection of Ap stars. The spectra have superior signal-to-noise ratio, resolution and wavelength coverage to those used previously. This combined with the ground-breaking inversion techniques introduced by Kochukhov et al. (2002) results in maps which represent the state-of-the-art in the field of stellar cartography. These maps will allow us to better understand the links between the magnetic field and the physical processes leading to the formation of chemical structures in the photosphere and allow us to address questions surrounding the detailed magnetic field geometry of Ap 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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".