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Record W2089097543 · doi:10.1088/0004-637x/783/1/58

TRACING THE OUTFLOW OF A<i>z</i>= 0.334 FeLoBAL: NEW CONSTRAINTS FROM LOW-IONIZATION ABSORBERS IN FBQS J1151+3822

2014· article· en· W2089097543 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsWestern University
Fundersnot available
KeywordsOutflowPhotoionizationQuasarAbsorption (acoustics)RADIUSIonizationLuminosityHydrogenLine (geometry)

Abstract

fetched live from OpenAlex

We show for the first time that FBQS J1151+3822 is an iron low-ionization broad absorption line quasar (FeLoBAL QSO), the second-brightest and second-closest known example of this class. He i * and Fe ii together act as an effective analytical tool, allowing us to obtain useful kinematic constraints from photoionization models of the outflow without needing to assume any particular acceleration model. The main outflow's log ionization parameter is −1.5, the log hydrogen density (cm −3 ) 5.5–8, the log hydrogen column density (cm −2 ) 21.7–21.9, the absorption radius 7.2–127 pc, and the kinetic luminosity is 0.16%–4.5% of the bolometric luminosity. We obtain line-of-sight covering fractions of ∼0.25 for strong Fe ii , ∼0.5 for He i *, and ∼0.6 for Mg ii . Narrower and shallower absorption lines from weaker Fe ii and Mn ii with an outflow velocity of ∼3400 km s −1 have appeared between 2005 and 2011, suggesting that dense cores may have condensed inside the main outflow. Consideration of the literature might suggest that the FBQS J1151+3822 outflow is a member of a rare and distinct subclass of FeLoBALs with high densities and correspondingly small absorption radii. We find, however, that such outflows are not necessarily a distinct subclass, and that their apparent rarity could be a symptom of selection bias in studies using density-sensitive lines.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.528

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 communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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

Citations50
Published2014
Admission routes1
Has abstractyes

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