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Record W2736729055 · doi:10.3847/1538-4357/aaa1ed

Elucidating ΛCDM: Impact of Baryon Acoustic Oscillation Measurements on the Hubble Constant Discrepancy

2018· article· en· W2736729055 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCosmic microwave backgroundHubble's lawCosmic distance ladderGalaxyCosmologyBaryon acoustic oscillationsBaryonOscillation (cell signaling)South Pole Telescope

Abstract

fetched live from OpenAlex

Abstract We examine the impact of baryon acoustic oscillation (BAO) scale measurements on the discrepancy between the value of the Hubble constant ( H 0 ) inferred from the local distance ladder and that from Planck cosmic microwave background (CMB) data. While the BAO data alone cannot constrain H 0 , we show that combining the latest BAO results with WMAP , Atacama Cosmology Telescope (ACT), or South Pole Telescope (SPT) CMB data produces values of H 0 that are lower than the distance ladder, independent of Planck , and that this downward pull was less apparent in some earlier analyses that used only angle-averaged BAO scale constraints rather than full anisotropic information. At the same time, the combination of BAO and CMB data also disfavors the lower values of H 0 preferred by the Planck high-multipole temperature power spectrum. Combining galaxy and Ly α forest BAO with a precise estimate of the primordial deuterium abundance produces km s −1 Mpc −1 for the flat model. This value is completely independent of CMB anisotropy constraints and is lower than the latest distance ladder constraint, although tension also exists between the galaxy BAO and Ly α BAO. These results show that it is not possible to explain the H 0 disagreement solely with a systematic error specific to the Planck data. The fact that tensions remain even after the removal of any single data set makes this intriguing puzzle all the more challenging to resolve.

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: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.409

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 communication0.0000.000
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 head0.023
GPT teacher head0.293
Teacher spread0.270 · 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

Citations232
Published2018
Admission routes1
Has abstractyes

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