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Record W7095673854

Preprint typeset using L ATEX style emulateapj v. 11/26/04 THE SL2S GALAXY-SCALE GRAVITATIONAL LENS SAMPLE. I. THE ALIGNMENT OF MASS AND LIGHT IN MASSIVE EARLY-TYPE GALAXIES AT Z = 0.2 − 0.9

2012· article· en· W7095673854 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Comparative Analysis Research
Canadian institutionsnot available
Fundersnot available
KeywordsGravitational lensGalaxyDark matterWeak gravitational lensingMass distributionStrong gravitational lensingGravitationTelescope
DOInot available

Abstract

fetched live from OpenAlex

We study the relative alignment of mass and light in a sample of 16 massive early-type galaxies at z = 0.2 − 0.9 that act as strong gravitational lenses. The sample was identified from deep multiband images obtained as part of the Canada France Hawaii Telescope Legacy Survey as part of the Strong Lensing Legacy Survey (SL2S). Higher resolution follow-up imaging is available for a subset of 10 systems. We construct gravitational lens models and infer total enclosed mass, elongation, and position angle of the mass distribution. By comparison with the observed distribution of light we infer that there is a substantial amount of external shear with mean value 〈γext 〉 = 0.12 ± 0.05, arising most likely from the environment of the SL2S lenses. In a companion paper, we combine these measurements with follow-up Keck spectroscopy to study the evolution of the stellar and dark matter content of early-type galaxies as a function of cosmic time. Subject headings: galaxies: fundamental parameters — gravitational lensing: strong lenging to measure accurately the relative distribution of baryonic and dark matter on sub-galactic scales. By-andlarge, traditional methods require the presence of a luminous

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)0.003
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 score0.118
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.103
GPT teacher head0.402
Teacher spread0.299 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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