The R-Process Alliance: First Release from the Northern Search for r-process-enhanced Metal-poor Stars in the Galactic Halo
Bibliographic record
Abstract
Abstract This paper presents the detailed abundances and r -process classifications of 126 newly identified metal-poor stars as part of an ongoing collaboration, the R -Process Alliance. The stars were identified as metal-poor candidates from the RAdial Velocity Experiment (RAVE) and were followed up at high spectral resolution ( R ∼ 31,500) with the 3.5 m telescope at Apache Point Observatory. The atmospheric parameters were determined spectroscopically from Fe i lines, taking into account non-LTE corrections and using differential abundances with respect to a set of standards. Of the 126 new stars, 124 have [Fe/H] < −1.5, 105 have [Fe/H] < −2.0, and 4 have [Fe/H] < −3.0. Nine new carbon-enhanced metal-poor stars have been discovered, three of which are enhanced in r -process elements. Abundances of neutron-capture elements reveal 60 new r -I stars (with +0.3 ≤ [Eu/Fe] ≤ +1.0 and [Ba/Eu] < 0) and 4 new r -II stars (with [Eu/Fe] > +1.0). Nineteen stars are found to exhibit a “limited- r ” signature ([Sr/Ba] > +0.5, [Ba/Eu] < 0). For the r -II stars, the second- and third-peak main r -process patterns are consistent with the r -process signature in other metal-poor stars and the Sun. The abundances of the light, α , and Fe-peak elements match those of typical Milky Way (MW) halo stars, except for one r -I star that has high Na and low Mg, characteristic of globular cluster stars. Parallaxes and proper motions from the second Gaia data release yield UVW space velocities for these stars that are consistent with membership in the MW halo. Intriguingly, all r -II and the majority of r -I stars have retrograde orbits, which may indicate an accretion origin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".