MétaCan
Menu
Back to cohort
Record W1995859527 · doi:10.1145/2786784.2795138

Eulerian-on-lagrangian cloth

2015· article· en· W1995859527 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDiscretizationEulerian pathLagrangianObject (grammar)Table (database)Enhanced Data Rates for GSM EvolutionEuler–Lagrange equationComputer scienceMotion (physics)Computer graphics (images)MathematicsGeometryMathematical analysisArtificial intelligence

Abstract

fetched live from OpenAlex

We present a new, Eulerian-on-Lagrangian approach for modeling cloth. When a cloth modeled using the traditional Lagrangian approach is moved around an object with sharp corners, such as the edge of a table, the cloth cannot always bend smoothly around the object because it can bend only at its nodes. With our method, these constraints are built into the discretization of the cloth, giving us an equation of motion that directly honors these constraints. This allows the cloth to bend and move smoothly around such constraints. We show how our method can efficiently handle challenging simulations, such as pulling a table cloth from under wine glasses without knocking them over.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.261

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.304
Teacher spread0.257 · 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