Identification of newly-discovered sources belonging to the 4th IBIS\n catalog and to the 54 months Palermo Swift/BAT catalog
Bibliographic record
Abstract
The most recent all-sky surveys performed with the INTEGRAL and SWIFT\nsatellites allowed the detection of more than 1500 sources in hard X-rays above\n20 keV. About one quarter of them has no obvious counterpart at other\nwavelengths and therefore could not be associated with any known class of\nhigh-energy emitting objects. Although cross-correlation with catalogues or\nsurveys at other wavelengths (especially soft X-rays) is of invaluable support\nin pinpointing the putative optical candidates, only accurate optical\nspectroscopy can reveal the true nature of these sources. With the aim of\nidentifying them, we started in 2004 an optical spectroscopy program which uses\ndata from several telescopes worldwide and which proved extremely successful,\nleading to the identification of about 200 INTEGRAL objects and nearly 130\nSwift sources. Here we want to present a summary of this identification work\nand an outlook of our preliminary results on identification of newly-discovered\nsources belonging to the 4th IBIS catalog and to the 54 months Palermo\nSwift/BAT catalog.\n
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".