Chemical cartography with LAMOST and <i>Gaia</i> reveal azimuthal and spiral structure in the Galactic disc
Bibliographic record
Abstract
ABSTRACT Chemical Cartography, or mapping, of our Galaxy has the potential to fully transform our view of its structure and formation. In this work, we use chemical cartography to explore the metallicity distribution of OBAF-type disc stars from the LAMOST survey and a complementary sample of disc giant stars from Gaia DR3. We use these samples to constrain the radial and vertical metallicity gradients across the Galactic disc. We also explore whether there are detectable azimuthal variations in the metallicity distribution on top of the radial gradient. For the OBAF-type star sample from LAMOST, we find a radial metallicity gradient of Δ[Fe/H]/ΔR ∼−0.078 ± 0.001 dex kpc−1 in the plane of the disc and a vertical metallicity gradient of Δ[Fe/H]/ΔZ ∼−0.15 ± 0.01 dex kpc−1 in the solar neighbourhood. The radial gradient becomes shallower with increasing vertical height, while the vertical gradient becomes shallower with increasing Galactocentric radius, consistent with other studies. We also find detectable spatially dependent azimuthal variations on top of the radial metallicity gradient at the level of ∼0.10 dex. Interestingly, the azimuthal variations appear be close to the Galactic spiral arms in one data set (Gaia DR3) but not the other (LAMOST). These results suggest that there is azimuthal structure in the Galactic metallicity distribution and that in some cases it is co-located with spiral arms.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".