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Record W1972460605 · doi:10.1088/2041-8205/739/2/l44

RED NUGGETS AT HIGH REDSHIFT: STRUCTURAL EVOLUTION OF QUIESCENT GALAXIES OVER 10 Gyr OF COSMIC HISTORY

2011· article· en· W1972460605 on OpenAlexaff
Ivana Damjanov, Roberto Abraham, Karl Glazebrook, Patrick J. McCarthy, Evelyn Caris, R. G. Carlberg, Hsiao‐Wen Chen, D. Crampton, Andrew W. Green, Inger Jørgensen, S. Juneau, D. Le Borgne, Ronald O. Marzke, Richard Murowinski, Kathy Roth, S. Savaglio, Haojing Yan

Bibliographic record

VenueThe Astrophysical Journal Letters · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsMcMaster UniversityHerzberg Institute of AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsAstrophysicsPhysicsRedshiftGalaxyAstronomyGalaxy formation and evolutionCOSMIC cancer databaseStellar massRADIUSRedshift surveyStar formation

Abstract

fetched live from OpenAlex

We present an analysis of the size growth seen in early-type galaxies over 10 Gyr of cosmic time. Our analysis is based on a homogeneous synthesis of published data from 16 spectroscopic surveys observed at similar spatial resolution, augmented by new measurements for galaxies in the Gemini Deep Deep Survey. In total, our sample contains structural data for 465 galaxies (mainly early-type) in the redshift range 0.2 < z < 2.7. The size evolution of passively evolving galaxies over this redshift range is gradual and continuous, with no evidence for an end or change to the process around z ~ 1, as has been hinted at by some surveys which analyze subsets of the data in isolation. The size growth appears to be independent of stellar mass, with the mass-normalized half-light radius scaling with redshift as Re (1 + z)–1.62 ± 0.34. Surprisingly, this power law seems to be in good agreement with the recently reported continuous size evolution of UV-bright galaxies in the redshift range z ~ 0.5-3.5. It is also in accordance with the predictions from recent theoretical models.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.185
Teacher spread0.177 · 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 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

Citations165
Published2011
Admission routes1
Has abstractyes

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