The Atari Disk, a Metal-poor Stellar Population in the Disk System of the Milky Way
Bibliographic record
Abstract
Abstract We have developed a chemodynamical approach to assign 36,010 metal-poor SkyMapper stars to various Galactic stellar populations. Using two independent techniques (velocity and action space behavior), Gaia EDR3 astrometry, and photometric metallicities, we selected stars with the characteristics of the “metal-weak” thick-disk population by minimizing contamination by the canonical thick disk or other Galactic structures. This sample comprises 7127 stars, spans a metallicity range of −3.50 < [Fe/H] < −0.8, and has a systematic rotational velocity of 〈V ϕ 〉 = 154 km s−1 that lags that of the thick disk. Orbital eccentricities have intermediate values between typical thick-disk and halo values. The scale length is h R = 2.48 − 0.05 + 0.05 kpc, and the scale height is h Z = 1.68 − 0.15 + 0.19 kpc. The metallicity distribution function is well fit by an exponential with a slope of Δ log N / Δ [ Fe / H ] = 1.13 ± 0.06 . Overall, we find a significant metal-poor component consisting of 261 SkyMapper stars with [Fe/H] < −2.0. While our sample contains only 11 stars with [Fe/H] ≲ −3.0, investigating the JINAbase compilation of metal-poor stars reveals another 18 such stars (five have [Fe/H] < −4.0) that kinematically belong to our sample. These distinct spatial, kinematic, and chemical characteristics strongly suggest that this metal-poor, phase-mixed kinematic sample represents an independent disk component with an accretion origin in which a massive dwarf galaxy radially plunged into the early Galactic disk. Going forward, we propose to call the metal-weak thick-disk population the Atari disk, given its likely accretion origin, and in reference to it sharing space with the Galactic thin and thick disks.
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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 | 0.001 | 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".