Searching for ZZ Ceti White Dwarfs in the Gaia Survey
Bibliographic record
Abstract
Abstract The Gaia satellite recently released parallax measurements for ∼260,000 high-confidence white dwarf candidates, allowing for precise measurements of their physical parameters. By combining these parallaxes with Pan-STARRS and u-band photometry, we measured the effective temperature and stellar mass for all white dwarfs in the Northern Hemisphere within 100 pc of the Sun, and identified a sample of ZZ Ceti white dwarf candidates within the so-called instability strip. We acquired high-speed photometric observations for 90 candidates using the PESTO camera attached to the 1.6 m telescope at the Mont-Mégantic Observatory. We report the discovery of 38 new ZZ Ceti stars, including two very rare ultramassive pulsators. We also identified five possibly variable stars within the strip, in addition to 47 objects that do not appear to show any photometric variability. However, several of those could be variable with an amplitude below our detection threshold, or could be located outside the instability strip due to errors in their photometric parameters. In the light of our results, we explore the trends of the dominant period and amplitude in the M– plane, and briefly discuss the question of the purity of the ZZ Ceti instability strip (i.e., a region devoid of non-variable stars).
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".