MétaCan
Menu
Back to cohort
Record W4393890440 · doi:10.5281/zenodo.7273031

Palomar 5 N-Body Simulation

2022· dataset· en· W4393890440 on OpenAlexaff
Jeremy J. Webb, Nathaniel Starkman, Jo Bovy

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typedataset
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Please cite https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.4978S Contained is an ECSV file of an N-body simulation, using the the direct N-body code NBODY6 (Aarseth 2006) to simulate the evolution of a Palomar 5-like globular cluster. The initial cluster is taken to be a Plummer model consisting of 100,000 stars and has a half-mast radius of 10 pc. Stellar masses follow a Kroupa initial mass function with the minimum and maximum stellar mass set to 0.1 and 50 solar masses respectively. Single stars evolve using the stellar evolution prescription of Hurley 2000 assuming a metallicity of Z=0.001 while binary stars, in the event that binaries form, follow Hurley 2002. The properties of the external tidal field were set to reflect MWPotential2014, from Bovy 2015, and is a good approximation of the Galactic potential (Bovy 2016). The specific linear combination of potentials is a spherical potential from a power-law density with an exponential cut-off Galactic bulge, an NFW dark matter halo, and a Miyamoto-Nagai disc. The model cluster was evolved for 12 Gyr with an initial position and velocity that resulted in it being located at the present day location of Palomar 5 at the end of the simulation. The final mass and mass function of the model cluster are comparable to the observed properties of Palomar 5, but the model cluster is too compact relative to Palomar 5, which is in the process of dissolving.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0430.007

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 head0.024
GPT teacher head0.235
Teacher spread0.211 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicSpacecraft and Cryogenic TechnologiesFrench-language works237,207