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Record W2603366441 · doi:10.1017/s1743921316012291

Probing Galactic Outskirts with Dragonfly

2016· article· en· W2603366441 on OpenAlexaff
Roberto Abraham, Allison Merritt, Jielai Zhang, Pieter van Dokkum, Charlie Conroy, Shany Danieli, Lamiya Mowla

Bibliographic record

VenueProceedings of the International Astronomical Union · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsAstrophysicsGalaxySpiral galaxyAstronomySurface brightnessElliptical galaxyDiscStarlightGalactic haloHaloStars

Abstract

fetched live from OpenAlex

Abstract We describe the challenges inherent to low surface brightness imaging and present some early results from the Dragonfly Nearby Galaxies survey. Wide field, ultra-low surface brightness imaging (μ g > 31 mag arcsec −2 ) of the first eight galaxies in the survey reveals a rich variety in the distribution of stars in the outskirts of luminous nearby galaxies. The mean stellar halo mass fraction is 0.009 ± 0.005 with a peak-to-peak scatter of a factor of > 100. Some galaxies in the sample feature strongly structured halos resembling that of M31, but three of the eight galaxies have halos that are completely undetected in our data. We conclude that spiral galaxies as a class exhibit a rich variety in stellar halo properties, implying that their assembly histories have been highly non-uniform. While the outskirts of some galaxies are dominated by halos with the rich substructures predicted by numerical simulations, in other cases the outermost parts of galaxies are simply the extrapolated smooth starlight from enormous stellar disks that closely trace neutral gas morphology out to around 20 scale lengths.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.325

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 communication0.0000.001
Open science0.0000.000
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 head0.005
GPT teacher head0.188
Teacher spread0.182 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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