Bibliographic record
Abstract
We report the identification of 26 cool DZ white dwarfs that lie across and below the main sequence in the Sloan Digital Sky Survey (SDSS) u-g vs. g-r two-color diagram; 21 of these stars are new discoveries. The sample was identified by visual inspection of all spectra of objects that fall below the main sequence in the two-color diagram, as well as by an automated search for characteristic spectral features over a large area in color space that included the main sequence. The spectra and photometry provided by the SDSS project are interpreted with model atmospheres, including all relevant metals. Effective temperatures and element abundances are determined, while the surface gravity has to be assumed and was fixed at the canonical value of log g = 8. These stars represent the extension of the well-known DZ sequence towards cooler temperatures and fill the gap around Teff = 6500 K present in a previous study. The metal abundances are similar to those in the hotter DZ, but the lowest abundances are missing, probably because of our selection procedures. The interpretation is complicated in terms of the accretion/diffusion scenario, because we do not know if accretion is still occurring or has ended long ago. Independent of that uncertainty, the masses of the metals currently present in the convection zones - and thus an absolute lower limit of the total accreted masses - of these stars are similar to the largest asteroids in our solar system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".