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Record W3196446611 · doi:10.21105/joss.03416

OGRe: An Object-Oriented General Relativity Package for Mathematica

2021· article· en· W3196446611 on OpenAlexaff

Bibliographic record

VenueThe Journal of Open Source Software · 2021
Typearticle
Languageen
FieldMathematics
TopicMathematical and Computational Methods
Canadian institutionsBrock University
Fundersnot available
KeywordsGeneral relativityTensor calculusTensor (intrinsic definition)Variety (cybernetics)Theory of relativityTensor fieldMathematics of general relativityDifferential geometry

Abstract

fetched live from OpenAlex

OGRe is a modern Mathematica package for differential geometry and tensor calculus. It can be used in a variety of contexts where tensor calculations are needed, in both mathematics and physics, but it is especially suitable for general relativity -the field of physics where tensors are most commonly and ubiquitously used. Whether the user is doing cutting-edge research in general relativity or just making first steps in learning the theory, the ability to manipulate tensors and perform tensor calculations quickly, easily, and intuitively will greatly simplify and accelerate their work.

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)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.160
Threshold uncertainty score0.536

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.006
Open science0.0050.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.1600.099

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 head0.098
GPT teacher head0.402
Teacher spread0.303 · 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
GenreSoftware

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

Citations20
Published2021
Admission routes1
Has abstractyes

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