Siena Galaxy Atlas 2020
Bibliographic record
Abstract
Abstract We present the 2020 version of the Siena Galaxy Atlas (SGA-2020), a multiwavelength optical and infrared imaging atlas of 383,620 nearby galaxies. The SGA-2020 uses optical grz imaging over ≈20,000 deg 2 from the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9 and infrared imaging in four bands (spanning 3.4–22 μ m) from the 6 year unWISE coadds; it is more than 95% complete for galaxies larger than R (26) ≈ 25″ and r < 18 measured at the 26 mag arcsec −2 isophote in the r band. The atlas delivers precise coordinates, multiwavelength mosaics, azimuthally averaged optical surface-brightness profiles, model images and photometry, and additional ancillary metadata for the full sample. Coupled with existing and forthcoming optical spectroscopy from the DESI, the SGA-2020 will facilitate new detailed studies of the star formation and mass assembly histories of nearby galaxies; enable precise measurements of the local velocity field via the Tully–Fisher and fundamental plane relations; serve as a reference sample of lasting legacy value for time-domain and multimessenger astronomical events; and more.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.070 |
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".