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Record W2929877533

Sequences of spanning trees for L-infinity Delaunay triangulations

2018· article· en· W2929877533 on OpenAlexafffund
Prosenjit Bose, María del Pilar Cano Vila, Rodrigo I. Silveira

Bibliographic record

VenueRECERCAT (Consorci de Serveis Universitaris de Catalunya) · 2018
Typearticle
Languageen
FieldComputer Science
TopicComputational Geometry and Mesh Generation
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaEuropean Commission
KeywordsDelaunay triangulationCombinatoricsSpanning treeMathematicsComputer scienceConstrained Delaunay triangulation
DOInot available

Abstract

fetched live from OpenAlex

We extend a known result about L2-Delaunay triangulations to L∞-Delaunay. Let TS be the set\nof all non-crossing spanning trees of a planar n-point set S. We prove that for each element T\nof TS, there exists a length-decreasing sequence of trees T0, . . . , Tk in the L∞-metric such that\nT0 = T, Tk = MST(S) and Ti does not cross Ti−1 for all i = 1, . . . , k, where MST(S) denotes\nthe minimum spanning tree of S in the L∞ metric. We also give an Ω(log n) lower bound for the\nlength of the sequence

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)0.001
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.275
Teacher spread0.247 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations0
Published2018
Admission routes2
Has abstractyes

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