The Messy Nature of Fiber Spectra: Star–Quasar Pairs Masquerading as Dual Type 1 AGNs
Bibliographic record
Abstract
Abstract Theoretical studies predict that the most significant growth of supermassive black holes (SMBHs) occurs in late-stage mergers, coinciding with the manifestation of dual active galactic nuclei (AGNs), and both major and minor mergers are expected to be important for dual AGN growth. In fact, dual AGNs in minor mergers should be signposts for efficient minor-merger-induced SMBH growth for both the more and less massive progenitor. We identified two candidate dual AGNs residing in apparent minor mergers with mass ratios of ∼1:7 and ∼1:30. Sloan Digital Sky Survey (SDSS) fiber spectra show broad and narrow emission lines in the primary nuclei of each merger while only a narrow [O iii] emission line and a broad and prominent Hα/[N ii] complex is observed in the secondary nuclei. The FWHMs of the broad Hα lines in the primary and secondary nuclei are inconsistent in each merger, suggesting that each nucleus in each merger hosts a Type 1 AGN. However, spatially resolved Large Binocular Telescope optical spectroscopy reveals rest-frame stellar absorption features, indicating the secondary sources are foreground stars and that the previously detected broad lines are likely the result of fiber spillover effects induced by the atmospheric seeing at the time of the SDSS observations. This study demonstrates for the first time that optical spectroscopic searches for Type 1/Type 1 pairs similarly suffer from fiber spillover effects as has been observed previously for Seyfert 2 dual AGN candidates. The presence of foreground stars may not have been clear if an instrument with more limited wavelength range or limited sensitivity had been used.
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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 | 0.002 | 0.001 |
| 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) | 0.002 | 0.000 |
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".