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Record W129480699

Local fairing with local inverse

2013· article· en· W129480699 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

VenueGraphics Interface · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Analysis Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSmoothingSubdivisionInverseLocal structureInterpretation (philosophy)Computer scienceMathematicsClass (philosophy)Domain (mathematical analysis)AlgorithmGeometryTopology (electrical circuits)Mathematical optimizationMathematical analysisCombinatoricsArtificial intelligenceEngineeringComputer visionPhysics
DOInot available

Abstract

fetched live from OpenAlex

Local fairing techniques are extensively used in the geometry processing of curves and surfaces. They also play an important role in the multiresolution shape editing and synthesis applications. However, due to the inter-dependency of the vertices after applying the current fairing techniques, their inverses are not local. Finding a local fairing operation with local inverse provides a well-defined relationship between the smooth vertices and the initial vertices. This paper introduces a new fairing operation for curves and surfaces that is smoothing and local but with a local inverse. In the curve domain, we find a class of banded smoothing matrices with banded inverses. Then, using the geometric interpretation of the corresponding local operation, this class is extended to surfaces. We discuss the advantages of using this new fairing operation in different applications. Also, the resulting operation is used to find novel subdivision schemes with well-defined reverse subdivisions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.603

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 science0.0000.000
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 head0.007
GPT teacher head0.218
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