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Record W3098060989

The association between gas and galaxies I: CFHT spectroscopy and pair analysis

2006· article· en· W3098060989 on OpenAlexaboutno aff

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsAstrophysicsAstronomyGalaxyDark galaxyGalaxy groupPeculiar galaxyRedshiftUniverseLuminous infrared galaxyGalaxy formation and evolutionRedshift surveyLenticular galaxy
DOInot available

Abstract

fetched live from OpenAlex

We investigate the relative distribution of the gaseous contents of the Universe (as traced by a sample of Lyman alpha (lya) absorbers), and the luminous baryonic matter (as traced by a redshift survey of galaxies in the same volume searched for lya absorbers), along 16 lines-of-sight (LOS) between redshifts 0 and 1. Our galaxy redshift survey was made with the Multi-Object Spectrograph (MOS) on Canada-France-Hawaii Telescope (CFHT) and, when combined with galaxies from the literature in the same LOS, gives us a galaxy sample of 636 objects. By combining this with an absorption line sample of 406 absorbing systems drawn from published works, we are able to study the relationship between gas and galaxies over the latter half of the age of the Universe. A correlation between absorbers and galaxies is detected out to separation of 1.5 Mpc. This correlation is weaker than the galaxy-galaxy correlation. There is also some evidence that the absorbing systems seen in CIV are more closely related to galaxies, although this correlation could be with column density rather than metallicity. The above results are all consistent with the absorbing gas and the galaxies co-existing in dark matter filaments and knots as predicted by current models, where the column density of the absorbing gas is correlated with the underlying matter density.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0010.000
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 head0.226
Teacher spread0.217 · 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

Citations19
Published2006
Admission routes1
Has abstractyes

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Same venueCERN Document Server (European Organization for Nuclear Research)Same topicGalaxies: Formation, Evolution, PhenomenaFrench-language works237,207