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A deep Chandra survey of the Groth Strip - II. Optical identification of the X-ray sources

2006· article· en· W1938133140 on OpenAlexaffabout
A. Georgakakis, K. Nandra, E. S. Laird, Stephen Gwyn, Charles C. Steidel, Vicki L. Sarajedini, P. Barmby, S. M. Faber, Alison L. Coil, Michael C. Cooper, Michael W. Davis, Jeffrey A. Newman

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPhysicsQSOSAstrophysicsRedshiftPhotometry (optics)GalaxyActive galactic nucleusQuasarPopulationAstronomyPhotometric redshiftStellar populationStar formationStars

Abstract

fetched live from OpenAlex

In this paper, we discuss the optical and X-ray spectral properties of the sources detected in a single 200-ks Chandra pointing in the Groth-Westphal Strip region. A wealth of optical photometric and spectroscopic data are available in this field providing optical identifications and redshift determinations for the X-ray population. The optical photometry and spectroscopy used here are primarily from the Deep Extragalactic Evolutionary Probe 2 (DEEP2) survey with additional redshifts obtained from the literature. These are complemented with the deeper (r ≈ 26 mag) multiwaveband data (ugriz) from the Canada–France–Hawaii Telescope Legacy Survey to estimate photometric redshifts and to optically identify sources fainter than the DEEP2 magnitude limit (R_(AB)≈ 24.5 mag). We focus our study on the 2–10 keV selected sample comprising 97 sources to the limit ≈ 8 × 10^(−1)6 erg s^(−1) cm^(−2), this being the most complete in terms of optical identification rate (86 per cent) and redshift determination fraction (63 per cent; both spectroscopic and photometric). We first construct the redshift distribution of the sample which shows a peak at z≈ 1. This is in broad agreement with models where less luminous active galactic nuclei (AGNs) evolve out to z≈ 1 with powerful quasi-stellar objects (QSOs) peaking at higher redshift, z≈ 2. Evolution similar to that of broad-line QSOs applied to the entire AGN population (both types I and II) does not fit the data. We also explore the observedNH distribution of the sample and estimate a fraction of obscured AGN (N_H > 10^(22) cm^(−2)) of 48 ± 9 per cent. This is found to be consistent with both a luminosity-dependent intrinsic N_H distribution, where less luminous systems comprise a higher fraction of type II AGNs and models with a fixed ratio 2:1 between types I and II AGNs. We further compare our results with those obtained in deeper and shallower surveys. We argue that a luminosity-dependent parametrization of the intrinsic NH distribution is required to account for the fraction of obscured AGN observed in different samples over a wide range of fluxes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.007
GPT teacher head0.188
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2006
Admission routes2
Has abstractyes

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