-XRT follow-up analysis of unidentified hard X-ray sources
Bibliographic record
Abstract
Context. It has been established that the sources contributing to the cosmic X-ray background (CXB) emission are mainly nearby active galactic nuclei (AGNs), in particular those that are obscured. Thus, it is important to fully identify the hard X-ray sky source population to accurately characterize the individual contribution of different AGNs to the overall CXB emission. Aims. We present a follow-up analysis of all 218 sources marked as unidentified in our previous revision of the third release of the Palermo Swift-BAT hard X-ray catalog (3PBC) based on our multifrequency classification scheme. These 218 sources were classified as unidentified in our previous analyses because they lacked an assigned low-energy counterpart. Methods. We searched for soft X-ray counterparts of these 218 3PBC sources in archival Swift-XRT observations obtained between January 1, 2005, and August 1, 2018. In particular, we found 1213 archival Swift-XRT observations for 192 of the 218 unidentified sources. Results. We find 93 possible Swift-XRT counterparts within the Swift-BAT positional uncertainty regions. They correspond to 73 3PBC sources, 60 of which have only a single Swift-XRT detection; the rest have multiple detections. We present all the detected possible counterparts of the as-of-yet-unidentified hard X-ray sources to the community as a catalog for future spectroscopic follow-up targets, together with a short catalog of our classification of the ten sources for which there were available spectra.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".