The Andromeda Optical and Infrared Disk Survey
Bibliographic record
Abstract
The Andromeda Optical and Infrared Disk Survey has mapped M31 in $u^* g^\prime r^\prime i^\prime J K_s$ wavelengths out to R=40 kpc using the MegaCam and WIRCam wide-field cameras on the Canada-France-Hawaii Telescope. Our survey is uniquely designed to simultaneously resolve stars while also carefully reproducing the surface brightness of M31, allowing us to study M31's global structure in the context of both resolved stellar populations and spectral energy distributions. We use the Elixir-LSB method to calibrate the optical $u^* g^\prime r^\prime i^\prime$ images by building real-time maps of the sky background with sky-target nodding. These maps are stable to $\mu_g \lesssim 28.5$ mag arcsec$^{-2}$ and reveal warps in the outer M31 disk in surface brightness. The equivalent WIRCam mapping in the near-infrared uses a combination of sky-target nodding and image-to-image sky offset optimization to produce stable surface brightnesses. This study enables a detailed analysis of the systematics of spectral energy distribution fitting with near-infrared bands where asymptotic giant branch stars impose a significant, but ill-constrained, contribution to the near-infrared light of a galaxy. Here we present panchromatic surface brightness maps and initial results from our near-infrared resolved stellar catalog.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".