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Record W2066612780 · doi:10.1145/1236246.1236306

Voronoi-Delaunay duality and Delaunay meshes

2007· article· en· W2066612780 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
TopicComputational Geometry and Mesh Generation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsVoronoi diagramDelaunay triangulationPolygon meshBowyer–Watson algorithmConstrained Delaunay triangulationComputer scienceCentroidal Voronoi tessellationMathematicsGeometryAlgorithmComputer graphics (images)

Abstract

fetched live from OpenAlex

In this paper, we are concerned with Delaunay triangulations of the vertex set of a piecewise flat (pwf) surface. We first propose the notion of well-formed Voronoi diagrams and establish a precise dual relationship between them and proper Delaunay triangulations on pwf surfaces. Then we provide an algorithm which, given any input manifold triangle mesh, constructs a Delaunay mesh: a manifold triangle mesh whose edges form an intrinsic Delaunay triangulation of its vertex set. Rather than relying on a geodesic Delaunay triangulation on the input mesh, our algorithm swaps the physical mesh edges based on the locally Delaunay criterion. We prove that when a physical edge that is not locally Delaunay is swapped, the surface area of the mesh is reduced. In order to ensure a proper Delaunay triangulation, some new vertices may need to be introduced, leading to a refinement scheme, and we detail the cases involved.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score0.293

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 studies0.0000.000
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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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