The <i>Pristine</i> survey II: A sample of bright stars observed with FEROS
Bibliographic record
Abstract
Extremely metal‐poor (EMP) stars are old objects formed in the first Gyr of the Universe. They are rare and, to select them the most successful strategy has been to build on large and low‐resolution spectroscopic surveys. The combination of narrow‐ and broad‐band photometry provides a powerful and cheaper alternative to select metal‐poor stars. The ongoing Pristine Survey is adopting this strategy, conducting photometry with the Canada France Hawaii Telescope MegaCam wide‐field imager and a narrow‐band filter centered at 395.2 nm on the Ca II‐H and ‐K lines. In this paper, we present the results of the spectroscopic follow‐up conducted on a sample of 26 stars at the bright end of the magnitude range of the Survey (g⩽15), using FEROS at the MPG/ESO 2.2‐m telescope (manufactured by Zeiss, Oberkochen, Germany). From our chemical investigation on the sample, we conclude that this magnitude range is too bright to use the Sloan Digital Sky Survey (SDSS) gri bands, which are typically saturated. Instead, the Pristine photometry can be usefully combined with the AAVSO Photometric All Sky Survey (APASS) griphotometry to provide reliable metallicity estimates.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".