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Record W2364690702

Collaborative and virtual architectural design in second life: FINC-AV experiment

2008· article· en· W2364690702 on OpenAlexaboutno aff
Jean-Pierre Goulette, Sandra Marques, Jean-Baptiste Boulanger, Pierre Côté

Bibliographic record

VenueIEEE International Technology Management Conference · 2008
Typearticle
Languageen
FieldEngineering
Topic3D Modeling in Geospatial Applications
Canadian institutionsnot available
Fundersnot available
KeywordsStudioArchitectureDesign studioContext (archaeology)Architectural designComputer scienceFocus (optics)Engineering design processProcess (computing)MultimediaHuman–computer interactionEngineeringArchitectural engineeringVisual artsTelecommunicationsArtOperating systemGeography
DOInot available

Abstract

fetched live from OpenAlex

The use and evolution of information and communication technologies is widening not only the process of communicating architecture but also it is challenging what we design and also how we design. The focus of this paper is to present and discuss a collaborative and virtual architectural design studio jointly undertaken by the Schools of Architecture of Toulouse in France, and Laval University in Quebec City, Canada, which was carried out during the Fall semester of 2007. In the context of our experiment, FINC-AV (Forme, Information, Novation, Conception — Architecture Virtuelle), activities are held by two geographically distant studios that communicate and coordinate design information and tasks using the multi-user networked 3D virtual world Second Life (SL).

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0030.002
Open science0.0030.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.023
GPT teacher head0.250
Teacher spread0.227 · 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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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