The SARAO MeerKAT 1.3 GHz Galactic Plane Survey
Bibliographic record
Abstract
ABSTRACT We present the SARAO MeerKAT Galactic Plane Survey (SMGPS), a 1.3 GHz continuum survey of almost half of the Galactic Plane (251° ≤l ≤ 358° and 2° ≤l ≤ 61° at |b| ≤ $1{_{.}^{\circ}}5$). SMGPS is the largest, most sensitive, and highest angular resolution 1 GHz survey of the plane yet carried out, with an angular resolution of 8 arcsec and a broad-band root-mean-square sensitivity of ∼10–20 μJy beam−1. Here, we describe the first publicly available data release from SMGPS which comprises data cubes of frequency-resolved images over 908–1656 MHz, power-law fits to the images, and broad-band zeroth moment integrated intensity images. A thorough assessment of the data quality and guidance for future usage of the data products are given. Finally, we discuss the tremendous potential of SMGPS by showcasing highlights of the Galactic and extragalactic science that it permits. These highlights include the discovery of a new population of non-thermal radio filaments; identification of new candidate supernova remnants, pulsar wind nebulae and planetary nebulae; improved radio/mid-infrared classification of rare luminous blue variables and discovery of associated extended radio nebulae; new radio stars identified by Bayesian cross-matching techniques; the realization that many of the largest radio-quiet Wide-field Infrared Survey Explorer (WISE) H ii region candidates are not true H ii regions; and a large sample of previously undiscovered background H i galaxies in the Zone of Avoidance.
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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 | 0.002 | 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) | 0.004 | 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".