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Record W1484532480 · doi:10.1051/0004-6361:20065154

Tracking quintessence by cosmic shear

2006· article· en· W1484532480 on OpenAlexafffund
C. Schimd, I. Tereno, Jean–Philippe Uzan, Y. Mellier, Ludovic Van Waerbeke, E. Semboloni, Henk Hoekstra, Liping Fu, Alain Riazuelo

Bibliographic record

VenueAstronomy and Astrophysics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
FundersCentre National de la Recherche ScientifiqueAgence Nationale de la RechercheNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced Research
KeywordsQuintessenceDark energyPhysicsCosmic microwave backgroundWeak gravitational lensingCOSMIC cancer databaseAstrophysicsScalar fieldTheoretical physicsCosmologyClassical mechanicsRedshiftGalaxy

Abstract

fetched live from OpenAlex

Aims.Dark energy can be investigated in two complementary ways, by considering either general parameterizations or physically well-defined models. Following the second route, we explore the observational constraints on quintessence models where the acceleration of our universe is driven by a slow-rolling scalar field. Using weak lensing data to investigate high-energy motivated models of dark energy for the first time, the analysis focuses on cosmic shear, examining how weak lensing surveys can constrain dark energy, discussing the limitations due to the lack of knowledge of the non-linear regime, and combining with type Ia supernovae data and cosmic microwave background observations to lift some degeneracies.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.493
Threshold uncertainty score0.683

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 studies0.0000.000
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 head0.004
GPT teacher head0.209
Teacher spread0.205 · 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 designTheoretical or conceptual
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

Citations73
Published2006
Admission routes2
Has abstractyes

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