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Record W3016205385 · doi:10.5281/zenodo.163795

Probing Agn Accretion History Through X-Ray Variability

2016· article· en· W3016205385 on OpenAlexfundno aff
M. Paolillo, I. E. Papadakis, W. N. Brandt, Yongquan Xue, Bin Luo, P. Tozzi, Ohad Shemmer, V. Allevato, F. E. Bauer, Anton M. Koekemoer, C. Vignali, Fabio Vito, Guang Yang, J. X. Wang, Xianzhong Zheng

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsnot available
FundersUniversity of WaterlooDartmouth CollegeJohns Hopkins UniversityUniversità degli Studi di Napoli Federico IICollege of Engineering, Michigan State UniversityGoddard Space Flight CenterSmithsonian InstitutionMichigan State UniversityEuropean Southern ObservatorySpace Telescope Science InstituteMassachusetts Institute of TechnologyPrinceton University
KeywordsAccretion (finance)GeologyAstrophysicsAstronomyPhysicsRemote sensingEnvironmental science

Abstract

fetched live from OpenAlex

I will present recent results on AGN variability in the CDFS survey. Using over 10 years of X-ray monitoring and comparison with local AGNs we are able to constrain the variability dependence on BH mass and accreton rate, and use it to trace the accretion hisory of the AGN population up to z=3.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.235
Teacher spread0.205 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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