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Record W2063109261 · doi:10.1086/426913

X-Ray Insights into Interpreting C<scp>iv</scp>Blueshifts and Optical/Ultraviolet Continua

2005· article· en· W2063109261 on OpenAlexaff
S. C. Gallagher, Gordon T. Richards, Patrick B. Hall, W. N. Brandt, Donald P. Schneider, D. E. vanden Berk

Bibliographic record

VenueThe Astronomical Journal · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsYork University
Fundersnot available
KeywordsQuasarAstrophysicsPhysicsRedshiftOVV quasarEmission spectrumBlueshiftUltravioletSpectral lineAbsorption (acoustics)AstronomyGalaxyOpticsPhotoluminescence

Abstract

fetched live from OpenAlex

We present 0.5-8.0 keV Chandra observations of six bright quasars that represent extrema in quasar emission-line properties -- three quasars each with small and large blueshifts of the CIV emission line with respect to the systemic redshift of the quasars. Supplemented with seven archival Chandra observations of quasars that met our selection criteria, we investigate the origin of this emission-line phenomenon in the general context of the structure of quasars. We find that the quasars with the largest CIV blueshifts show evidence, from joint-spectral fitting, for intrinsic X-ray absorption (N_H ~ 10^22 cm^-2). Given the lack of accompanying CIV absorption, this gas is likely to be highly ionized, and may be identified with the shielding gas in the disk-wind paradigm. Furthermore, we find evidence for a correlation of alpha_uv, the ultraviolet spectral index, with the hardness of the X-ray continuum; an analysis of independent Bright Quasar Survey data from the literature supports this conclusion. This result points to intrinsically red quasars having systematically flatter hard X-ray continua without evidence for X-ray absorption. We speculate on the origins of these correlations of X-ray properties with both CIV blueshift and alpha_uv and discuss the implications for models of quasar structure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.205
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations39
Published2005
Admission routes1
Has abstractyes

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