The ASKAP-EMU Early Science Project: 888 MHz radio continuum survey of the Large Magellanic Cloud
Bibliographic record
Abstract
ABSTRACT We present an analysis of a new 120 deg2 radio continuum image of the Large Magellanic Cloud (LMC) at 888 MHz with a bandwidth of 288 MHz and beam size of 13${_{.}^{\prime\prime}}$9 × 12${_{.}^{\prime\prime}}$1 from the Australian Square Kilometre Array Pathfinder processed as part of the Evolutionary Map of the Universe survey. The median root mean squared noise is 58 $\mu$Jy beam−1. We present a catalogue of 54 612 sources, divided over a Gold list (30 866 sources) complete down to 0.5 mJy uniformly across the field, a Silver list (22 080 sources) reaching down to <0.2 mJy, and a Bronze list (1666 sources) of visually inspected sources in areas of high noise and/or near bright complex emission. We discuss detections of planetary nebulae and their radio luminosity function, young stellar objects showing a correlation between radio luminosity and gas temperature, novae and X-ray binaries in the LMC, and active stars in the Galactic foreground that may become a significant population below this flux level. We present examples of diffuse emission in the LMC (H ii regions, supernova remnants, bubbles) and distant galaxies showcasing spectacular interaction between jets and intracluster medium. Among 14 333 infrared counterparts of the predominantly background radio source population, we find that star-forming galaxies become more prominent below 3 mJy compared to active galactic nuclei. We combine the new 888 MHz data with archival Australia Telescope Compact Array data at 1.4 GHz to determine spectral indices; the vast majority display synchrotron emission but flatter spectra occur too. We argue that the most extreme spectral index values are due to variability.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".