The ASKAP EMU Early Science Project: radio continuum survey of the Small Magellanic Cloud
Bibliographic record
Abstract
ABSTRACT We present two new radio continuum images from the Australian Square Kilometre Array Pathfinder (ASKAP) survey in the direction of the Small Magellanic Cloud (SMC). These images are part of the Evolutionary Map of the Universe (EMU) Early Science Project (ESP) survey of the Small and Large Magellanic Clouds. The two new source lists produced from these images contain radio continuum sources observed at 960 MHz (4489 sources) and 1320 MHz (5954 sources) with a bandwidth of 192 MHz and beam sizes of 30.0 × 30.0 arcsec2 and 16.3 × 15.1 arcsec2, respectively. The median root mean square (RMS) noise values are 186 $\mu$Jy beam−1 (960 MHz) and 165 $\mu$Jy beam−1 (1320 MHz). To create point source catalogues, we use these two source lists, together with the previously published Molonglo Observatory Synthesis Telescope (MOST) and the Australia Telescope Compact Array (ATCA) point source catalogues to estimate spectral indices for the whole population of radio point sources found in the survey region. Combining our ASKAP catalogues with these radio continuum surveys, we found 7736 point-like sources in common over an area of 30 deg2. In addition, we report the detection of two new, low surface brightness supernova remnant candidates in the SMC. The high sensitivity of the new ASKAP ESP survey also enabled us to detect the bright end of the SMC planetary nebula sample, with 22 out of 102 optically known planetary nebulae showing point-like radio continuum emission. Lastly, we present several morphologically interesting background radio galaxies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".