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Record W2210698333 · doi:10.1260/1478-0771.13.3-4.237

Hybrid Representation: Intaglio Etching of Digital Models

2015· article· en· W2210698333 on OpenAlexaff
Johan Voordouw

Bibliographic record

VenueInternational Journal of Architectural Computing · 2015
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsCarleton University
Fundersnot available
KeywordsRepresentation (politics)StudioComputer graphics (images)Computer scienceSoftwareEngineering drawingSet (abstract data type)Modular designArchitectureComputer architectureProgramming languageEngineeringVisual artsArtTelecommunications

Abstract

fetched live from OpenAlex

This paper explores an alternative approach to architectural representation by using computation and digital modeling to develop novel modes of drawing. The project was initiated for the International Architecture Biennale Rotterdam (IABR 2014) and was exhibited in the seminal Kunsthal Rotterdam in the summer of 2014. The project, entitled Weerkas, was a set of twelve intaglio etchings. A combination of digital modeling programs such as Rhino, Grasshopper and 3D Studio Max and drafting software AutoCAD were used to develop the drawings. The digital files were photo-transferred and etched using a polymer intaglio plate. The analog/digital hybrid explores the limitations of such a combined means of expression and its possible significance in developing a two from three-dimensional drawing technique.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.033
GPT teacher head0.271
Teacher spread0.238 · 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 designBench or experimental
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
Published2015
Admission routes1
Has abstractyes

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