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Record W3101164871 · doi:10.25916/sut.26229650.v1

The 2dF Galaxy Redshift Survey: Spherical harmonics analysis of fluctuations in the final catalogue

2004· article· en· W3101164871 on OpenAlexaff
Will J. Percival, Daniel Burkey, Alan Heavens, Andy Taylor, Shaun Cole, J. A. Peacock, C. M. Baugh, Joss Bland‐Hawthorn, Terry Bridges, Russell Cannon, Matthew Colless, C. A. Collins, W. J. Couch, Gavin Dalton, Simon P. Driver, G. Efstathiou, Richard S. Ellis, Carlos S. Frenk, Karl Glazebrook, Carole Jackson, O. Lahav, Ian Lewis, S. L. Lumsden, S. Maddox, P. Norberg, B. A. Peterson, William J. Sutherland, Keith Taylor

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsQueen's University
Fundersnot available
KeywordsPhysicsAstrophysicsRedshiftGalaxyHarmonicsRedshift surveyAstronomyQuantum mechanics

Abstract

fetched live from OpenAlex

We present the result of a decomposition of the 2dF Galaxy Redshift Survey (2dFGRS) galaxy overdensity field into an orthonormal basis of spherical harmonics and spherical Bessel functions. Galaxies are expected to directly follow the bulk motion of the density field on large scales, so the absolute amplitude of the observed large-scale redshift-space distortions caused by this motion is expected to be independent of galaxy properties. By splitting the overdensity field into radial and angular components, we linearly model the observed distortion and obtain the cosmological constraint Ω m0.6σ8 = 0.46 ± 0.06. The amplitude of the linear redshift-space distortions relative to the galaxy overdensity field is dependent on galaxy properties and, for L* galaxies at redshift z = 0, we measure β(L*, 0) = 0.58 ± 0.08, and the amplitude of the overdensity fluctuations b(L *, 0)σ8 = 0.79 ± 0.03, marginalizing over the power spectrum shape parameters. Assuming a fixed power spectrum shape consistent with the full Fourier analysis produces very similar parameter constraints.

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)0.001
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 score0.030
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.247
Teacher spread0.227 · 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

Citations146
Published2004
Admission routes1
Has abstractyes

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