A Composite Extreme‐Ultraviolet QSO Spectrum from<i>FUSE</i>
Bibliographic record
Abstract
The Far Ultraviolet Spectroscopic Explorer ( FUSE ) has surveyed a large sample (>100) of active galactic nuclei (AGNs) in the low-redshift universe ( z < 1). Its response at short wavelengths makes it possible to measure directly the far-ultraviolet spectral properties of quasi-stellar objects (QSOs) and Seyfert 1 galaxies at z < 0.3. Using archival FUSE spectra, we form a composite extreme-ultraviolet (EUV) spectrum of QSOs at z ≤ 0.67. After consideration of many possible sources of systematic error in our analysis, we find that the spectral slope of the FUSE composite spectrum, α = -0.56 for F ν ∝ ν α , is significantly harder than the EUV (λ ≲ 1200 Å) portion of the composite spectrum of QSOs with z > 0.33 formed from archival Hubble Space Telescope ( HST ) spectra, α = -1.76 ± 0.12. We identify several prominent emission lines in the FUSE composite and find that the high-ionization O VI and Ne VIII emission lines are enhanced relative to the HST composite. Power-law continuum fits to the individual FUSE AGN spectra reveal a correlation between EUV spectral slope and AGN luminosity in the FUSE and FUSE + HST samples, in the sense that lower luminosity AGNs show harder spectral slopes. We find an anticorrelation between the hardness of the EUV spectral slope and AGN black hole mass, using estimates of this quantity found in the literature. We interpret these results in the context of the well-known anticorrelation between AGN luminosity and emission-line strength, the Baldwin effect, given that the median luminosity of the FUSE AGN sample is an order of magnitude lower than that of the HST sample.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".