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Record W2120251897 · doi:10.1145/581316.581318

Using computer algebra methods to determine the chemical dimension of finitely ramified Sierpinski carpets

2002· article· en· W2120251897 on OpenAlexaff
Astrid Franz, Christian Schulzky, Karl Heinz Hoffmann

Bibliographic record

VenueACM SIGSAM Bulletin · 2002
Typearticle
Languageen
FieldComputer Science
TopicTopological and Geometric Data Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsDimension (graph theory)MathematicsSierpinski carpetHausdorff dimensionDijkstra's algorithmExponentSierpinski triangleScalingShortest path problemCombinatoricsPath (computing)Pure mathematicsDiscrete mathematicsMathematical analysisComputer scienceGeometryFractal

Abstract

fetched live from OpenAlex

We present a new algorithm for calculating the chemical dimension d 1 of finitely ramified Sierpinski carpets. Using an algorithm of Dijkstra, we compute iteratively, using Mathematica , the shortest paths through a carpet. The scaling exponent of the lengths of these shortest paths over the linear size of the carpet is d min the minimum path dimension, which is related to the chemical dimension.

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)0.006
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.002
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 head0.086
GPT teacher head0.314
Teacher spread0.228 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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