Geometry of the Large Magellanic Cloud Disk: Results from MACHO and the Two Micron All Sky Survey
Bibliographic record
Abstract
We present a detailed study of the viewing angles and geometry of the inner LMC (ρ ≲ 4°) based on a sample of more than 2000 MACHO Cepheids with complete { VR } KC light curves and single-phase Two Micron All Sky Survey (2MASS) JHK s observations. The sample is considerably larger than any previously studied subset of LMC Cepheids and has an improved areal coverage. Single-epoch random-phase 2MASS photometry is corrected using MACHO V light curves to derive mean JHK s magnitudes. We analyze the resulting period-luminosity relations in VRJHK s to recover statistical reddening and distance to each individual Cepheid, with respect to the mean distance modulus and reddening of the LMC. By fitting a plane solution to the derived individual distance moduli, the values of LMC viewing angles are obtained: position angle θ = 151 0 ± 2 4, inclination i = 30 7 ± 1 1. In the so-called ring analysis, we find a strong dependence of the derived viewing angles on the adopted center of the LMC, which we interpret as being due to deviations from planar geometry. Analysis of residuals from the plane fit indicates the presence of a symmetric warp in the LMC disk and the bar elevated above the disk plane. Nonplanar geometry of the inner LMC explains a broad range for values of i and θ in the literature and suggests caution when deriving viewing angles from inner LMC data.
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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 | 0.001 |
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".