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Record W7117570503 · doi:10.2298/saj2511009k

New askap radio-continuum surveys of the small magellanic cloud

2025· article· en· W7117570503 on OpenAlexaff
O.K. Khattab, M. D. Filipović, Z.J. Smeaton, R.Z.E. Alsaberi, Crawford Ej, D. A. Leahy, S. Dai, N. Rajabpour

Bibliographic record

VenueSerbian Astronomical Journal · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPathfinderSkyPoint sourceTelescopeSmall Magellanic CloudGalaxyLarge Magellanic CloudPoint (geometry)

Abstract

fetched live from OpenAlex

We present two new radio-continuum images from the Australian Square Kilometre Array Pathfinder (ASKAP) POLarisation Sky Survey of the Universe's Magnetism (POSSUM) survey in the direction of the Small Magellanic Cloud (SMC). The two new source lists produced from these images contain 36,571 radio continuum sources observed at 944 MHz and 15,227 sources at 1367 MHz, with beam sizes of 14''.5 \times 12''.2 and 8''.7 \times 8''.2 , respectively. We used the Aegean software to create these point source catalogues, and together with the previously published Meer-Karoo Array Telescope (MeerKAT) point source catalogue, we estimated spectral indices for the whole population of radio point sources in common. By cross-matching our ASKAP catalogues with the MeerKAT catalogue, we found 21,442 and 12,654 point sources in common for 944 MHz and 1367 MHz, respectively, within a 2'' region. This point source catalogue will help to further our knowledge of the SMC and highlights the power of the new generation of telescopes such as ASKAP in studying different galactic populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.006
GPT teacher head0.207
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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