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Record W3208204202 · doi:10.5281/zenodo.5168868

OGRe: An Object-Oriented General Relativity Package for Mathematica

2021· article· en· W3208204202 on OpenAlexaff
Barak Shoshany

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsBrock University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

v1.6 (2021-08-07) New modules: TCalcGeodesicFromChristoffel: Creates a new rank-1 tensor object containing the geodesic equations obtained for each of the coordinates using the Christoffel symbols of the given metric: ẍσ + Γσμνẋμẋν = 0. The Christoffel symbols will be calculated automatically using TCalcChristoffel if they have not already been calculated. TCalcGeodesicFromLagrangian: Creates a new rank-1 tensor object containing the geodesic equations obtained for each of the coordinates by applying the Euler-Lagrange equations to the curve Lagrangian. The Lagrangian will be calculated automatically using TCalcLagrangian (see below) if it has not already been calculated. This module leaves the derivatives with respect to the curve parameter in the Euler-Lagrange equation unevaluated (using Inactive), which can sometimes help solve the geodesic equations by inspection. Use Activate to evaluate the derivatives. (Recall that TList and TShow can apply a function to the tensor's components before displaying them, so you can write e.g. TList["ID", Activate].) Often the equations obtained in this way will be different from the ones obtained using TCalcGeodesicFromChristoffel, but they will always have the same solutions. Usually, one of TCalcGeodesicFromChristoffel or TCalcGeodesicFromLagrangian will generate simpler equations for a given metric and/or coordinate system. TCalcLagrangian: Calculates the curve Lagrangian of a metric, defined as the norm-squared of the tangent to the curve: gμνẋμẋν. Taking the square root of (the absolute value of) the Lagrangian yields the integrand of the curve length functional. Varying the Lagrangian using the Euler-Lagrange equations yields the geodesic equations (see TCalcGeodesicFromLagrangian above). TMessage: Not really a module, just a placeholder symbol to which messages not associated with any specific OGRe module are attached. In particular, when a private module (called only internally within the package) invokes Message, the message will now be displayed as TMessage:: instead of the awkward OGRe`Private` :: . Not all modules use TMessage yet; the transition will be performed gradually in the upcoming releases. TSetAllowOverwrite: Allows or disallows overwriting tensors. The default value is False, which means you cannot create a new tensor with the same ID as an existing tensor. Calling TSetAllowOverwrite[True] will allow overwriting tensors, which is more convenient, but can result in loss of data. You will be warned whenever a tensor is being overwritten, but this warning can be turned off (like any other Message) using Off[TMessage::WarningOverwrite]. This setting is persistent between sessions. TSetCurveParameter: Sets the curve parameter used by TCalcGeodesicFromChristoffel, TCalcGeodesicFromLagrangian, and TCalcLagrangian. These modules will produce results in terms of the coordinate symbols as functions of the curve parameter and their derivatives with respect to this parameter. The default value is λ. If the Lagrangian or geodesic equation vector is displayed using TList or TShow, the arguments of the coordinate functions are omitted (e.g. x instead of x[λ]) and derivatives with respect to the curve parameter are displayed in Newton (dot) notation (e.g. ẋ instead of x'[λ]) for improved readability. However, extracting the components using TGetComponents will produce the full expressions (e.g. to be used with DSolve). When the curve parameter is changed, the parameter of the coordinate functions in all of the tensors calculated so far will be changed accordingly. TSetReservedSymbols: Works similar to TInitializeSymbols, which has now been removed. However, TSetReservedSymbols also saves the reserved symbols so they can be exported and then imported in a later session. If the reserved symbol is a function of the coordinates, TList and TShow will not show the arguments of the function when displaying the components of a tensor, for improved readability. TVolumeElementSquared: Calculates the determinant of a given metric. The square root of the determinant (or its negative, for a pseudo-Riemannian metric) is the volume element. Changes to existing modules: All TCalc* modules now check if the metric exists first. TGetComponents: This module now gets the components of the tensor in the default index configuration and/or coordinate system if either or both are not specified. However, if the default value is used, a message will let you know which representation the components are given in, to avoid confusion. TInitializeSymbols has been removed and replaced with TSetReservedSymbols (see above). TList and TShow: Partial derivatives are now displayed in compact notation for improved readability. TList will no longer list the same element twice if it is non-zero but equal to minus itself (e.g. ComplexInfinity). See TSetCurveParameter and TSetReservedSymbols above for other changes. TNewMetric: If the new metric overrides a previous metric with the same ID, all of the curvature tensors calculated from the metric being overwritten will be automatically deleted, for consistency. TSetParallelization: Now uses $MaxLicenseSubprocesses instead of the deprecated (as of Mathematica 12.3) $ConfiguredKernels to determine how many kernels to launch when enabling parallelization. Disabling parallelization now also closes the kernels. Tensor simplifications will no longer invoke parallelization if the tensor only has one component, to avoid unnecessary overhead. Other changes: A button to open the GitHub repository directly in Visual Studio Code has been added to the badges in README.md. This release is dedicated to my grandfather Yona Shoshany, who taught me BASIC, my first programming language, in my early childhood. He passed away a day before this release was published.

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)0.007
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 score0.295
Threshold uncertainty score0.986

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0060.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.2950.204

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 head0.049
GPT teacher head0.314
Teacher spread0.266 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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