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Record W2028119574 · doi:10.1051/0004-6361/201423585

Flux- and volume-limited groups/clusters for the SDSS galaxies: catalogues and mass estimation

2014· article· en· W2028119574 on OpenAlexfundno aff

Bibliographic record

VenueAstronomy and Astrophysics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryYork UniversityInstituto de Astrofísica de CanariasEesti TeadusagentuurCarnegie Mellon UniversityUniversity of ArizonaOffice of ScienceJohns Hopkins UniversityCollege of Engineering, Michigan State UniversityHarvard UniversityOhio State UniversityNew Mexico State UniversityUniversity of PortsmouthYale UniversityVanderbilt UniversityNational Science FoundationUniversity of WashingtonAlfred P. Sloan FoundationNational Aeronautics and Space AdministrationPrinceton UniversityBrookhaven National LaboratoryU.S. Department of Energy
KeywordsGalaxySkyRadial velocityGalaxy clusterCompleteness (order theory)Galaxy groupCluster (spacecraft)Galaxy groups and clusters

Abstract

fetched live from OpenAlex

We provide flux- and volume-limited galaxy group and cluster catalogues based on the spectroscopic sample of the galaxies of SDSS data release 10. We used a modified friends-of-friends method with a variable linking length in the transverse and radial directions to identify as many realistic groups as possible. The flux-limited catalogue incorporates galaxies down to mr = 17.77 mag. It includes 588 193 galaxies and 82 458 groups. The volume-limited catalogues are complete for absolute magnitudes down to Mr,lim = −18.0, −18.5, −19.0, −19.5, −20.0, −20.5, and −21.0; the completeness is achieved within different spatial volumes. Our analysis shows that flux- and volume-limited group samples are well compatible, especially for the larger groups/clusters. Dynamical mass estimates based on radial velocity dispersions and group extent in the sky were added to the extracted groups.

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 score0.387
Threshold uncertainty score0.902

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 studies0.0010.000
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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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

Citations240
Published2014
Admission routes1
Has abstractyes

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