A Suzaku sample of unabsorbed narrow-line and broad-line Seyfert 1 galaxies – II. Iron emission and absorption
Bibliographic record
Abstract
ABSTRACT A sample of 22 narrow-line type 1 Seyfert (NLS1) and 47 broad-line type 1 Seyfert (BLS1) galaxies observed with Suzaku is used to examine the Fe K-band properties of each group. Three different models are used to examine the presence of: narrow neutral Fe K α line at $6.4{\rm \, keV}$ and ionized Fe xxv and Fe xxvi emission lines (model A); a broad emission feature at around $6{-}7{\rm \, keV}$ (model B); and an absorption edge at ${\sim}7.1{\rm \, keV}$ (model C). In all three models, the neutral Fe K α line is weaker (lower luminosity and equivalent width) in NLS1s than in BLS1s. Model (B) also finds a more significant broad component (larger equivalent width) in NLS1s than in BLS1s. The feature does not appear to be an artifact of steeper spectra in NLS1s, but rather an intrinsic property of these sources. From model (C), the optical depth of the absorption edge appears comparable between the two samples. When comparing the absorption with the emission line properties, NLS1s seem to exhibit a lower ratio of emission-to-absorption of iron than BLS1s, and have a lower value than expected based on the fluorescence yield. The observed differences may arise from different torus geometries (e.g. larger opening angle in NLS1s), and/or additional sources of Fe K emission and absorption in NLS1s beyond pure fluorescence (e.g. originating in the disc and broad-line region).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".