GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey II: Galactic plane 345° <<i>l</i>< 67°, 180° <<i>l</i>< 240°
Bibliographic record
Abstract
Abstract This work makes available a further $2\,860~\text{deg}^2$ of the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey, covering half of the accessible galactic plane, across 20 frequency bands sampling 72–231 MHz, with resolution $4\,\text{arcmin}-2\,\text{arcmin}$ . Unlike previous GLEAM data releases, we used multi-scaleCLEANto better deconvolve large-scale galactic structure. For the galactic longitude ranges $345^\circ < l < 67^\circ$ , $180^\circ < l < 240^\circ$ , we provide a compact source catalogue of 22 037 components selected from a 60-MHz bandwidth image centred at 200 MHz, with RMS noise $\approx10-20\,\text{mJy}\,\text{beam}^{-1}$ and position accuracy better than 2 arcsec. The catalogue has a completeness of 50% at ${\approx}120\,\text{mJy}$ , and a reliability of 99.86%. It covers galactic latitudes $1^\circ\leq|b|\leq10^\circ$ towards the galactic centre and $|b|\leq10^\circ$ for other regions, and is available from Vizier; images covering $|b|\leq10^\circ$ for all longitudes are made available on the GLEAM Virtual Observatory (VO).server and SkyView.
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 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 | 0.004 |
| 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) | 0.018 | 0.010 |
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".