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Record W6929355152 · doi:10.48550/arxiv.2503.17341

Structure and kinematics of the interacting group NGC 5098/5096

2025· preprint· en· W6929355152 on OpenAlexaboutno aff

Bibliographic record

VenuearXiv (Cornell University) · 2025
Typepreprint
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsnot available
Fundersnot available
KeywordsSubstructureSurface brightnessGalaxyRedshiftCompact groupHubble sequenceUniverseBrightnessKinematics

Abstract

fetched live from OpenAlex

Most galaxies in the Universe are found in groups, which have various morphologies and dynamical states. Studying how groups evolve is an important step for our understanding in both large-scale structure formation and galaxy evolution. We analysed the system composed by two groups at z = 0.037, NGC 5098, a group dominated by a pair of elliptical galaxies, and NGC 5096, a compact system which appears to be interacting with NGC 5098. We aim to describe its current dynamical state in order to investigate how it fits in our current cosmological framework. Our analysis is based on deep Canada-France-Hawaii Telescope (CFHT/MegaCam) g and r imaging, archival Chandra X-ray data, and publicly available data of the galaxy redshift distribution. We model the surface brightness of the 12 brightest galaxies in the field-of-view and investigate the diffuse intragroup light that we detect. With a redshift sample of 112 galaxies, we study the dynamical states of both groups. We detect low surface brightness diffuse light associated with both galaxy-galaxy interactions and a possible group-group collision. The substructure we found in velocity space indicates a past interaction between both groups. This is further corroborated by the X-ray analysis. We conclude that NGC 5098 and NGC 5096 form a complex system, that may have collided in the past, producing a sloshing observed in X-rays and a large scale diffuse component of intragroup light as well as some important tidal debris.

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)0.001
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 score0.590
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.097
GPT teacher head0.263
Teacher spread0.166 · 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
Published2025
Admission routes1
Has abstractyes

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