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Record W2580880899 · doi:10.3847/1538-4357/836/1/67

Galactic Dark Matter Halos and Globular Cluster Populations. III. Extension to Extreme Environments

2017· article· en· W2580880899 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of WaterlooHerzberg Institute of AstrophysicsMcMaster University
Fundersnot available
KeywordsGlobular clusterGalaxyDark matterMilky WayGalaxy clusterGalaxy groups and clustersCluster (spacecraft)Dark matter haloHalo

Abstract

fetched live from OpenAlex

Abstract The total mass in the globular cluster (GC) system of a galaxy is empirically a near-constant fraction of the total mass of the galaxy across a range of 10 5 in galaxy mass. This trend is radically unlike the strongly nonlinear behavior of total stellar mass M ⋆ versus M h . We discuss extensions of this trend to two more extreme situations: (a) entire clusters of galaxies and (b) the ultra-diffuse galaxies (UDGs) recently discovered in Coma and elsewhere. Our calibration of the ratio from normal galaxies, accounting for new revisions in the adopted mass-to-light ratio for GCs, now gives as the mean absolute mass fraction. We find that the same ratio appears valid for galaxy clusters and UDGs. Estimates of in the four clusters we examine tend to be slightly higher than for individual galaxies, but more data and better constraints on the mean GC mass in such systems are needed to determine if this difference is significant. We use the constancy of to estimate total masses for several individual cases; for example, the total mass of the Milky Way is calculated to be . Physical explanations for the uniformity of are still descriptive, but point to a picture in which massive dense star clusters in their formation stages were relatively immune to the feedback that more strongly influenced lower-density regions where most stars form.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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

Citations156
Published2017
Admission routes1
Has abstractyes

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