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Implications of the remarkable homogeneity of galaxy groups and clusters

2010· article· en· W2952226681 on OpenAlexaff

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGalaxySkyPhotometry (optics)Mass distributionHomogeneity (statistics)Galaxy groupAccretion (finance)Galaxy formation and evolutionStar formation

Abstract

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Abstract We measure the diversity of galaxy groups and clusters with mass M > 1013h−1 M⊙, in terms of the star formation history of their galaxy populations, for the purpose of constraining the mass scale at which environmentally important processes play a role in galaxy evolution. We consider three different group catalogues, selected in different ways, with photometry and spectroscopy from the Sloan Digital Sky Survey. For each system, we measure the fraction of passively evolving galaxies within R200 and brighter than either Mr=−18 (and with z < 0.05) or Mr=−20 (and z < 0.1). We use the (u−g) and (r−i) galaxy colours to distinguish between star-forming and passively evolving galaxies. By considering the binomial distribution expected from the observed number of members in each cluster, we are able to either recover the intrinsic scatter in this fraction or put robust 95 per cent confidence upper limits on its value. The intrinsic standard deviation in the fraction of passive galaxies is consistent with a small value of ≲0.1 in most mass bins for all three samples. There is no strong trend with mass; even groups with M∼ 1013h−1 M⊙ are consistent with such a small, intrinsic distribution. We compare these results with theoretical models of the accretion history to show that, if environment plays a role in transforming galaxies, such effects must occur first at mass scales far below that of rich clusters, at most M∼ 1013 M⊙.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.005
GPT teacher head0.185
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations27
Published2010
Admission routes1
Has abstractyes

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