The surface chemistry of the magnetic Ap star HD 147010★
Bibliographic record
Abstract
HD 147010 is a hot (Teff = 13 000 K), large-field magnetic Ap star that is a member of the Upper Scorpius–Centaurus Association, which means it is a star with a well-defined age (log t = 6.70). We offer a comprehensive analysis of the magnetic field and surface chemistry of HD 147010 based on seven spectra obtained using CFHT's ESPaDOnS spectropolarimeter. This data set is sufficient to obtain a first-order model of the magnetic field and obtain the abundance distribution of He, O, Mg, Al, Si, Ca, Ti, Cr, Fe, Ni, Sr, La, Ce, Pr, Nd and Sm. The magnetic field model is a low-order multipole expansion based on the variations of the line of sight and surface magnetic fields with rotation. Spectral synthesis was carried out using zeeman, a program which takes into account the influence of the magnetic field. A simple model of uniform abundance in each of two rings in the observed magnetic hemisphere with equal spans in colatitude was used. The new magnetic field measurements enabled us to re-analyse the rotation period of HD 147010, finding P = 3.9207 ± 0.0003 d. The line of sight and surface magnetic field strengths vary from about −2000 to −5000 G and 11000 to 17000 G, respectively. Our analysis finds large overabundances of Fe-peak and rare-earth elements relative to the solar ratios. In all cases, where strong variability in surface chemistry is observed, abundances are higher near the magnetic equator as compared to the magnetic pole. HD 147010 appears to be an Ap star that is highly rich in rare-earth elements that are of the order of 105 times more abundant than in the Sun. This analysis adds to the growing number of hot Ap stars for which both the magnetic field and abundance distribution have been studied in detail.
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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 | 0.000 | 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".