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Record W4385875962 · doi:10.21203/rs.3.rs-3246739/v1

Addressing the missing mass problem in galaxy clusters that is found with MOND-type theories

2023· preprint· en· W4385875962 on OpenAlexaff
A. Raymond Penner

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsPhysicsGravitationAstrophysicsGalaxy clusterMass distributionGravitational fieldGalaxyBaryonType (biology)Distribution (mathematics)Field (mathematics)Theoretical physicsAstronomy

Abstract

fetched live from OpenAlex

Abstract The MOND-type theories of AQUAdratic Lagrangian (AQUAL) and GRavitational Anti- Screening (GRAS) are applied to galaxy clusters. It will be shown that treating the baryonic mass distribution of the intracluster gas as being continuous leads to neglecting an important contribution to the clusters overall gravitational field. This is the localized mass density distribution that falls out from the theory which surrounds the protons within the gas. Including this contributor leads to an additional boost of approximately 60% to the gravitational field of clusters, over what MOND-type theories have previously been taken to provide. This accounts for most, if not all, of the shortfall of gravity or mass that has been attributed to clusters when MOND-type theories are used.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.006
Scholarly communication0.0030.004
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.152
GPT teacher head0.414
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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