The Pristine survey – IX. CFHT ESPaDOnS spectroscopic analysis of 115 bright metal-poor candidate stars
Bibliographic record
Abstract
ABSTRACT A chemo-dynamical analysis of 115 metal-poor candidate stars selected from the narrow-band Pristine photometric survey is presented based on CFHT high-resolution ESPaDOnS spectroscopy. We have discovered 28 new bright (V < 15) stars with [Fe/H] < −2.5 and 5 with [Fe/H] < −3.0 for success rates of 40 (28/70) and 19 per cent (5/27), respectively. A detailed model atmosphere analysis is carried out for the 28 new metal-poor stars. Stellar parameters were determined from SDSS photometric colours, Gaia DR2 parallaxes, MESA/MIST stellar isochrones, and the initial Pristine survey metallicities, following a Bayesian inference method. Chemical abundances are determined for 10 elements (Na, Mg, Ca, Sc, Ti, Cr, Fe, Ni, Y, and Ba). Most stars show chemical abundance patterns that are similar to the normal metal-poor stars in the Galactic halo; however, we also report the discoveries of a new r-process-rich star, a new CEMP-s candidate with [Y/Ba] > 0, and a metal-poor star with very low [Mg/Fe]. The kinematics and orbits for all of the highly probable metal-poor candidates are determined by combining our precision radial velocities with Gaia DR2 proper motions. Some stars show unusual kinematics for their chemistries, including planar orbits, unbound orbits, and highly elliptical orbits that plunge deeply into the Galactic bulge (Rperi < 0.5 kpc); also, eight stars have orbital energies and actions consistent with the Gaia-Enceladus accretion event. This paper contributes to our understanding of the complex chemo-dynamics of the metal-poor Galaxy, and increases the number of known bright metal-poor stars available for detailed nucleosynthetic studies.
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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 | 0.000 |
| 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".