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Record W2079821572 · doi:10.2752/147597504778052702

Textiles, Patterns and Technology: Digital Tools for the Geometric Analysis of Cloth and Culture

2004· article· en· W2079821572 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

VenueTEXTILE · 2004
Typearticle
Languageen
FieldEngineering
Topic3D Shape Modeling and Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsPlan (archaeology)Variety (cybernetics)Perspective (graphical)Computer scienceGeometric patternData scienceTextile designEngineering drawingMultimediaHuman–computer interactionArtificial intelligenceEngineeringVisual artsGeographyArtCAD

Abstract

fetched live from OpenAlex

Advances in information technology now provide a variety of digital tools for the mathematical investigation of the visual complexity of textile patterns and decorative designs. In this article, we report on innovative applications of this technology to the geometric analysis of Kuba cloth and Zillij mosaics. From our perspective, these objects present distinctly different analytical challenges, and typify problematic aspects of the classification and generation problems of artistic design. Mathematical considerations led us to use neural networks, shape grammars, and related technologies to approach these problems. Our ultimate goal is to use our methods, samples, and peripherals to build an interactive database for the study of historical patterns and the generation of contemporary designs. Details of our research plan can be found in Kolak Dudek et al. 2003: 129–35).

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: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.215
Teacher spread0.205 · 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