A systematic survey for <i>z</i>&lt; 0.04 CLAGNs
Bibliographic record
Abstract
ABSTRACT We have conducted a systematic survey for z < 0.04 active Galactic nuclei (AGNs) that may have changed spectral class over the past decade. We use SkyMapper, Pan-STARRS and the Véron-Cetty & Véron catalogue to search the entire sky for these ‘changing-look’ AGNs (CLAGNs) using a variety of selection methods, where Pan-STARRS has a coverage of 3$\pi$ steradians (sky north of Declination −30○) and SkyMapper has coverage of ∼21000 $~\rm {deg^2}$ (sky south of Declination 0○). We use small aperture photometry to measure how colour and flux have changed over time, where a change may indicate a change in spectral type. Optical colour and flux are used as a proxy for changing Hα equivalent width, while WISE 3.4 μm flux is used to look for changes in the hot dust component. We have identified four AGNs with varying spectra selected using our optical colour selection method. Three AGNs were confirmed from recent observations with WiFeS on the 2.3 m telescope at Siding Spring and the other was identified from archival spectra alone. From this, we identify two new CLAGNs; NGC 1346 and 2MASX J20075129–1108346. We also recover Mrk 915 and Mrk 609, which are known to have varying spectra in the literature, but they do not meet our specific criteria for CLAGNs.
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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 | 0.000 |
| Bibliometrics | 0.006 | 0.002 |
| 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) | 0.002 | 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".