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Record W3210456485 · doi:10.5281/zenodo.3678601

NuGrid/NuDocker: A virtual research environment for computational nuclear and stellar astrophysics

2020· article· en· W3210456485 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNuclear astrophysicsAstronomyComputer sciencePhysicsAstrophysics

Abstract

fetched live from OpenAlex

The motivation behind NuDocker is to conserve the capability of running nuclear and stellar astrophysics simulations codes from many years ago, even if the commonly adapted compute environment has evolved (compilers, OS utilities, libraries). Thus the main goal of NuDocker is <strong>reproducibility of science</strong>. The stellar evolution code MESA and the NuGrid post-processing codes are <em>big</em> code instruments with lots of modules and dependencies that all have to play perfectly together. Rich Townsend's MESA SDK has significantly taken the pain out of compiling such codes. Nevertheless, it is still difficult to maintain on one actual computer the capability to run different versions of MESA, especially going back to the older versions. At the same time, a lot of important results have been obtained with these older revisions which in many cases are not obsolete, but just different MESA flavours.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.050
GPT teacher head0.244
Teacher spread0.193 · 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