SDSS DR7 WHITE DWARF CATALOG
Bibliographic record
Abstract
We present a new catalog of spectroscopically confirmed white dwarf stars from the Sloan Digital Sky Survey (SDSS) Data Release 7 spectroscopic catalog. We find 20,407 white dwarf spectra, representing 19,712 stars, and provide atmospheric model fits to 14,120 DA and 1011 DB white dwarf spectra from 12,843 and 923 stars, respectively. These numbers represent more than a factor of two increase in the total number of white dwarf stars from the previous SDSS white dwarf catalogs based on DR4 data. Our distribution of subtypes varies from previous catalogs due to our more conservative, manual classifications of each star in our catalog, supplementing our automatic fits. In particular, we find a large number of magnetic white dwarf stars whose small Zeeman splittings mimic increased Stark broadening that would otherwise result in an overestimated log g if fit as a non-magnetic white dwarf. We calculate mean DA and DB masses for our clean, non-magnetic sample and find the DB mean mass is statistically larger than that for the DAs.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.031 |
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".