Multiband optical variability of a newly discovered 12 blazars sample from 2013–2019
Bibliographic record
Abstract
ABSTRACT Here we present the first optical photometric monitoring results of a sample of 12 newly discovered blazars from the ICRF – Gaia CRF astrometric link. The observations were performed from April 2013 to August 2019 using eight telescopes located in Europe. For a robust test for the brightness and colour variability, we use Abbé criterion and F-test. Moreover, linear fittings are performed to investigate the relation in the colour-magnitude variations of the blazars. Variability was confirmed in the case of 10 sources; two sources, 1429+249 and 1556+335 seem to be possibly variable. Three sources (1034+574, 1722+119, and 1741+597) have displayed large amplitude brightness change of more than one magnitude. We found that the seven sources displayed bluer-when-brighter variations, and one source showed redder-when-brighter variations. We briefly explain the various AGN emission models which can explain our results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".