Spectra and Polarisation In Cutouts of Extragalactic sources from RACS First Data Release (SPICE-RACS-DR1)
Bibliographic record
Abstract
*NOTICE* July 2024: We have discovered an error in the flux density of Stokes Q and U in this data release. Full details are provided in a corrigendum in PASA (see link below). If you are reading this notice the catalogue, spectra and images in this collection have been corrected. The data in the linked 'full' DAP collection are also corrected. Users of the old data can apply their own correction by multiplying Stokes Q and U by 2 for correct results. However, we recommend using the updated products provided here. Users can confirm they are using updated files by inspecting the HISTORY card in the FITS headers. Spectra and Polarisation In Cutouts of Extragalactic sources from RACS (SPICE-RACS) is a project to derive an all-Southern-sky, linear polarisation map from the Rapid ASKAP Continuum Survey (RACS). Through this project, we will derive the following products: - Cutout image cubes in Stokes I, Q, and U around every source detected in total intensity as a function of frequency - Polarisation spectra as a function of frequency and Faraday depth for every component detected in total intensity - A catalogue summarising the polarisation properties, including rotation measure (RM), for every component. This collection represents a subset of the data presented in SPICE-RACS-DR1 (Thomson et al. 2023). This subset refers to the 24680 components ('cut') (out of the 'full' 105912) for which a reliable polynomial fit could be derived for the Stokes I spectra that were extracted. This collection contains the 'cut' subset, please see the linked collections for the 'full' data. Our final data products are as follows: spice-racs.dr1.corrected.{cut,full}.xml: - Our component catalogue in VOTable format for the first (cut) and second (full) sets of components described above. The former is included with this deposit. {source_id}.cutout.{image,weights}.*.fits: - Image and weights cube cutout in Stokes I, Q, and U cutout around a RACS-low source identified by ‘source_id’. The data dimensions are J2000 right ascension and declination, Stokes parameter, and frequency. {cat_id}_polspec.fits: - Polarisation spectra extracted on the position of the RACS-low component identified by ‘cat_id’ in POLSPECTRA format. Each table contains a single row, corresponding to the component. spice_racs_dr1_polspec_{cut,full}.tar: - A tarball containing all of the POLSPECTRA for the 'cut' and second 'full' sets of components described above. These are available in the linked collections. Recommended catalogue subsets: Our 'full' catalogue contains extracted polarisation data for all 105912 Stokes I components detected in our DR1 region. It is important to note that the majority of these do not have reliably detected polarised emission. When using this catalogue please use the provided flags, and uncertainty/quality metrics to derive a subset suitable for your science goals. If you're unsure where to start, these are our recommended basic subsets: - 'goodI' : Where our Stokes I model is reliable -- channel_flag and stokesI_fit_flag are False (this produces the 'cut' catalogue from the 'full'). - 'goodL': Where we have a reliable detection of polarised signal, but not necessarily a reliable RM -- goodI plus leakage_flag is False and snr_polint >= 5. - 'goodRM': Where the RM is reliable -- goodL plus snr_flag is False.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".