THE DISCOVERY OF THE MOST METAL-RICH WHITE DWARF: COMPOSITION OF A TIDALLY DISRUPTED EXTRASOLAR DWARF PLANET
Bibliographic record
Abstract
Cool white dwarf stars are usually found to have an outer atmosphere that is practically pure in hydrogen or helium. However, a small fraction have traces of heavy elements that must originate from the accretion of extrinsic material, most probably circumstellar matter. Upon examining thousands of Sloan Digital Sky Survey (SDSS) spectra, we discovered that the helium-atmosphere white dwarf SDSS J073842.56+183509.6 shows the most severe metal pollution ever seen in the outermost layers of such stars. We present here a quantitative analysis of this exciting star by combining high signal-to-noise ratio follow-up spectroscopic and photometric observations with model atmospheres and evolutionary models. We determine the global structural properties of our target star, as well as the abundances of the most significant pollutants in its atmosphere, i.e., H, O, Na, Mg, Si, Ca, and Fe. The relative abundances of these elements imply that the source of the accreted material has a composition similar to that of Bulk Earth. We also report the signature of a circumstellar disk revealed through a large infrared excess in JHK photometry. Combined with our inferred estimate of the mass of the accreted material, this strongly suggests that we are witnessing the remains of a tidally disrupted extrasolar body that was as large as Ceres.
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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 | 0.000 | 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) | 0.000 | 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".