**FULL TITLE** ASP Conference Series, Vol. **VOLUME**, **YEAR OF PUBLICATION** **NAMES OF EDITORS** A Progress Report on the Empirical Determination of the ZZ Ceti Instability Strip
Bibliographic record
Abstract
Abstract. Although the Sloan Digital Sky Survey has permitted the discovery of an increasing number of new ZZ Ceti stars, recent published analyses have shown that there are still many relatively bright (V < 17) ZZ Ceti stars waiting to be found. We will discuss the discovery of several such objects in addition to a number of DA stars in which we detected no photometric variations. These were uncovered as part of an ongoing spectroscopic survey of DA white dwarfs from the McCook & Sion Catalog. By determining the atmospheric parameters of a large sample of DA stars, we were able to identify objects placed within or near the empirical boundaries of the ZZ Ceti instability strip. By establishing the photometric status of these stars, we can use them in an effort to conclusively pin down the empirical boundaries of the ZZ Ceti instability strip. 1. Ongoing Survey of the McCook & Sion Catalog Since the early 1990s, our group in Montreal has been carrying out a systematic study aimed at defining the empirical boundaries of the ZZ Ceti instability strip. We use quantitative time-averaged optical spectroscopy to pin down the
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.219 | 0.179 |
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".