Discovery of a Cool, Massive, and Metal-rich DAZ White Dwarf
Bibliographic record
Abstract
We report the discovery of a new metal-rich DAZ white dwarf, GD 362. High signal-to-noise ratio optical spectroscopy reveals the presence of spectral lines from hydrogen as well as Ca I, Ca II, Mg I, and Fe I. A detailed model atmosphere analysis of this star yields an effective temperature of T eff = 9740 ± 50 K, a surface gravity of log g = 9.12 ± 0.07, and photospheric abundances of log = -5.2 ± 0.1, log = -4.8 ± 0.1, and log = -4.5 ± 0.1. White dwarf cooling models are used to derive a mass of 1.24 M ☉ for GD 362, making it the most massive and metal-rich DAZ star uncovered to date. The problems related to the presence of such large metal abundances in a nearby ( d ~ 25 pc) white dwarf in terms of an accretion scenario are briefly discussed.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".