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Record W3155566642 · doi:10.20382/jocg.v13i2a5

Orientation preserving maps of the n × n grid

2022· article· en· W3155566642 on OpenAlexvenueno aff
Imre Bárány, Attila Pór, Pável Valtr

Bibliographic record

VenueJournal of Computational Geometry (Carleton University) · 2022
Typearticle
Languageen
FieldComputer Science
TopicComputational Geometry and Mesh Generation
Canadian institutionsnot available
Fundersnot available
KeywordsOrientation (vector space)GridComputer scienceGeometryMathematics

Abstract

fetched live from OpenAlex

For a finite set $A\subset \mathbb{R}^2$, a map $\varphi: A \to \mathbb{R}^2$ is orientation preserving if for every non-collinear triple $u,v,w \in A$ the orientation of the triangle $u,v,w$ is the same as that of the triangle $\varphi(u),\varphi(v),\varphi(w)$. We prove that for every $n \in \mathbb{N}$ and for every $\varepsilon>0$ there is $N=N(n,\varepsilon)\in \mathbb{N}$ such that the following holds. Assume that $\varphi :G(N)\to \mathbb{R}^2$ is an orientation preserving map where $G(N)$ is the grid $\{(i,j)\in \mathbb{Z}: -N \le i,j\le N\}$. Then there is an affine transformation $\psi :\mathbb{R}^2 \to \mathbb{R}^2$ and $z_0 \in \mathbb{Z}$ such that $z_0+G(n)\subset G(N)$ and $\|\psi \circ \varphi (z)-z\|<\varepsilon$ for every $z \in z_0+G(n)$. This result was previously proved in a completely different way by Nešetřil and Valtr, without obtaining any bound on $N$. Our proof gives $N(n,\varepsilon)=O(n^4\varepsilon^{-2})$.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.672
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.197
Teacher spread0.187 · 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 teacher head, 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
Published2022
Admission routes1
Has abstractyes

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