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Record W4403795666 · doi:10.48550/arxiv.2409.17371

Implications of the Milky Way Declining Rotation Curve

2024· preprint· en· W4403795666 on OpenAlexfundno aff
J. W. Moffat, H. Sharron, Viktor T. Toth

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
FundersInstitut Périmètre de physique théoriqueIndustry CanadaGovernment of Canada
KeywordsMilky WayRotation (mathematics)Galaxy rotation curveAstrophysicsAstronomyGeographyPhysicsMathematicsGeometryGalaxyGalaxy formation and evolution

Abstract

fetched live from OpenAlex

Almost all spiral galaxies have been observed to have flattening rotation curves. The new Gaia DR3 released data shows a Milky Way sharply Keplerian declining rotation curve, starting at $\sim 16$ kpc and ending at 26.5 kpc. The data reduces the total Milky Way mass by an order of magnitude, $M=2.06\times 10^{11}M_{\odot}$, compared to the standard required dark matter halo mass, $(2-5)\times10^{12}M_\odot$. Newtonian and modified gravity (MOG) fits are applied to the Gaia DR3 rotation curve data. The fit obtained using MOG has a total mass of $M\sim1.3\times 10^{11}M_{\odot}$, while the Newtonian fit predicts a mass of $M\sim2\times 10^{11}M_{\odot}$. These are in excess of the estimated visible baryon mass of the Milky Way, $M_b\sim (0.6-1.0)\times 10^{11}M_{\odot}$. It is possible that if the cicumgalactic (CGM) plasma-gas continues to be confirmed experimentally, then the additional baryon mass required to account for the estimated total Milky Way mass could be attributed to the CGM hot plasma-gas halo.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.096
GPT teacher head0.199
Teacher spread0.102 · 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
Published2024
Admission routes1
Has abstractyes

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