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Record W3201499007 · doi:10.5281/zenodo.4249877

Resolving the dust structures in AGNs using thermal-infrared Interferometry

2020· article· en· W3201499007 on OpenAlexaboutno aff
Leo Burtscher

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2020
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsnot available
Fundersnot available
KeywordsInterferometryInfraredRemote sensingThermal infraredEnvironmental scienceOpticsPhysicsGeology

Abstract

fetched live from OpenAlex

Active galactic nuclei (AGNs) are among the most luminous mid-infrared (MIR) emitters in the universe. In nearby AGNs, this emission is mostly from warm dust on scales of a tenth to about 10 parsec. This dust surrounds the accretion disk and absorbs its light along half of all lines of sight. While the structure and dynamics of this dust are still largely unknown, it has become clear in recent years that the "torus" picture is too simplistic since the majority of MIR emitting dust is actually located in the outflow direction rather than in the equatorial plane of the AGN. I will summarise the science highlights from AGN observations in the MIR at the highest angular resolution, in particular with long-baseline optical interferometry. I will also discuss the discovery space for future high-resolution studies with VLTI/MATISSE and ELT/METIS.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.624

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 science0.0010.001
Research integrity0.0000.000
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 head0.037
GPT teacher head0.274
Teacher spread0.237 · 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 designSimulation or modeling
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
Published2020
Admission routes1
Has abstractyes

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