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Record W6969029325 · doi:10.5281/zenodo.6364484

ELT/METIS and the AGN torus

2022· article· en· W6969029325 on OpenAlexaboutno aff

Bibliographic record

VenueLeiden Repository (Leiden University) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSpectrographEmission spectrumSpectroscopySpectral resolutionTorusInfraredJames Webb Space TelescopeThermal emissionWavelength

Abstract

fetched live from OpenAlex

The Mid-infrared E-ELT Thermal Infrared imager and Spectrograph (METIS) is one of the three first-light instruments selected for the European Extremely Large Telescope (ELT) and will cover the thermal infrared wavelength range, from ca. 3 - 13 microns. It will be a versatile instrument featuring diffraction-limited imaging and long-slit spectroscopy in the L/M and N bands as well as high spectral resolution (R ~ 100,000) integral field spectroscopy in the L and M bands. Its spatial resolution of 25 (70) mas in the L (N) band corresponds to a linear scale of 1 (3) parsec in nearby (10 Mpc) galaxies. For nearby AGNs, METIS forms the missing link between JWST and ground-based interferometry in both resolution and sensitivity. METIS will primarily observe continuum emission from dust at 100-800 K, but it will also be sensitive to the emission lines in this wavelength range, e.g. Brackett alpha, coronal lines like [SiIX] and [ArVI] and [AlVI], molecular lines of CO and H2O, and broad silicate emission and absorption lines. As such it is well matched to tackle several of the outstanding questions in current AGN research including "What triggers AGN activity?" and "How do AGN outflows connect to the host galaxy?". In this talk, I review METIS' instrumental capabilities with a particular focus on the prospects for AGN research.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.003
GPT teacher head0.156
Teacher spread0.153 · 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.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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