<i>Swift</i>observations of unidentified radio sources in the revised Third Cambridge Catalogue
Bibliographic record
Abstract
We have investigated a group of unassociated radio sources included in the Third Cambridge Catalogue (3CR) to increase the multifrequency information on them and possibly obtain an identification. We have carried out an observational campaign with the Swift satellite to observe with the Ultraviolet/Optical Telescope (UVOT) and the X-Ray Telescope (XRT) the field of view of 21 bright NRAO VLA Sky Survey (NVSS) sources within the positional uncertainty region of the 3CR sources. Furthermore, we have searched in the recent AllWISE Source Catalogue for infrared sources matching the position of these NVSS sources. We have detected significant emission in the soft X-ray band for nine of the investigated NVSS sources. To all of them, and in four cases with no soft X-ray association, we have associated a Wide-field Infrared Survey Explorer infrared counterpart. Eight of these infrared candidates have not been proposed earlier in the literature. In the five remaining cases our candidate matches one among a few optical candidates suggested for the same 3CR source in previous studies. No source has been detected in the UVOT filters at the position of the NVSS objects, confirming the scenario that all of them are heavily obscured. With this in mind, a spectroscopic campaign, preferably in the infrared band, will be necessary to establish the nature of the sources that we have finally identified.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".