ALMA Band 3 polarimetric follow-up of a complete sample of faint PACO sources
Bibliographic record
Abstract
Abstract We present Atacama Large Millimetre/submillimiter Array (ALMA) high sensitivity ($\sigma _\mathrm{ P} \simeq 0.4\,$ mJy) polarimetric observations at $97.5\,$ GHz (Band 3) of a complete sample of 32 extragalactic radio sources drawn from the faint Planck–ATCA Co-eval Observations (PACO) sample (b < −75°, compact sources brighter than $200\,$ mJy at $20\,$ GHz). We achieved a detection rate of $~97\, {\rm per\, cent}$ at $3\, \sigma$ (only 1 non-detection). We complement these observations with new Australia Telescope Compact Array (ATCA) data between 2.1 and $35\,$GHz obtained within a few months and with data published in earlier papers from our collaboration. Adding the co-eval GaLactic and Extragalactic All-sky Murchison widefield array (GLEAM) survey detections between $70\,$ and $230\,$ MHz for our sources, we present spectra over more than 3 decades in frequency in total intensity and over about 1.7 decades in polarization. The spectra of our sources are smooth over the whole frequency range, with no sign of dust emission from the host galaxy at mm wavelengths or of a sharp high frequency decline due, for example, to electron ageing. We do however find indications of multiple emitting components and present a classification based on the number of detected components. We analyse the polarization fraction behaviour and distributions up to $97\,$ GHz for different source classes. Source counts in polarization are presented at $95\,$ GHz.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".