What Does the LMC Look Like? It Depends on [M/H] and Age
Bibliographic record
Abstract
Abstract We offer a new way to look at the LMC through stellar mono-abundance and mono-age mono-abundance maps. These maps are based on ≳500,000 member stars with estimates of [M/H] (σ [M/H] ~ 0.17) and age ( σ log τ ~ 0.15 ), derived from Gaia Data Release 3 XP spectra and photometry, which are tied to and validated against APOGEE. This results in the first area-complete, metallicity- and age-differentiated stellar maps of any disk galaxy. Azimuthally averaged, these maps reveal a surprisingly simple picture of the Milky Way's largest satellite galaxy. For any [M/H] below −0.1 dex, the LMC's radial profile is well described by a simple exponential, but with a scale length that steadily shrinks toward higher metallicities, from nearly 2.3 kpc at [M/H] = −1.8 to only 0.75 kpc at [M/H] = −0.25, as fit by forward modeling the spatial distribution of mono-[M/H] populations. The prominence of the bar decreases dramatically with [M/H], making it barely discernible at [M/H] ≲ −1.5. Yet, even for metal-rich populations, the bar has little impact on the azimuthally averaged profile of the mono-abundance components. Including ages, we find that the scale length is a greater function of age than of metallicity, with younger populations far more centrally concentrated. Only at old ages does the scale length change, specifically decrease, with increasing metallicity. These findings provide quantitative support for a scenario in which the LMC built its stellar structure effectively outside-in.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".