The SARAO MeerKAT Galactic Plane Survey filamentary source catalogue
Bibliographic record
Abstract
ABSTRACT We present a catalogue of filamentary structures identified in the SARAO (South African Radio Astronomy Observatory) MeerKAT 1.3 GHz Galactic Plane Survey (SMGPS). We extract 933 filaments across the survey area, 803 of which (${\sim }86~{{\ \rm per\ cent}}$) are associated with extended radio structures (e.g. supernova remnants and H ii regions), while 130 (${\sim }14~{{\ \rm per\ cent}}$) are largely isolated. We classify filaments as thermal or non-thermal via their associated mid-infrared emission and find that 77/130 (${\sim }59~{{\ \rm per\ cent}}$) of the isolated sources are likely to be non-thermal, and are therefore excellent candidates for the first isolated, non-thermal radio filaments observed outside of the Galactic Centre (GC). Comparing the morphological properties of these non-thermal candidates to the non-thermal filaments observed towards the GC, we find that the GC filaments are on the whole angularly narrower and shorter than those across the SMGPS, potentially an effect of distance. The SMGPS filaments have flux densities similar to those of the GC; however, the distribution of the latter extends to higher flux densities. If the SMGPS filaments were closer than the GC population, it would imply a more energetic population of cosmic ray electrons in the GC. We find that the filament position angles in the SMGPS are uniformly distributed, implying that the local magnetic field traced by the filaments does not follow the large-scale Galactic field. Finally, although we have clearly shown that filaments are not unique to the GC, the GC nevertheless has the highest density of filaments in the Milky Way.
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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 | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".