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Record W4301904680 · doi:10.52842/conf.ecaade.2006.710

A Theory of Artistry for 3D Data Fusion - The element of craft in digital reconstruction

2006· article· en· W4301904680 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueeCAADe proceedings · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceVisualizationRendering (computer graphics)DocumentationAbstractionExternal Data RepresentationComputer graphics (images)Computer visionProcess (computing)Protocol (science)Interpolation (computer graphics)Artificial intelligenceHuman–computer interactionAnimation

Abstract

fetched live from OpenAlex

The following paper will articulate through an urban renewal proposal project for an area in Montréal, Canada that uses a “3D imaging and modeling protocol” and that accounts for the interaction between mediation and making in digitizing and constructing existing conditions digital artifacts. The protocol incorporates multi-sensor technologies with modeling and rendering techniques through a process of interpolation between a heterogeneous set of existing photographic, physical, and 2D documentation. The mode of operation implemented is a multi-layered and hybrid approach that recognizes the interplay between human scale and perception, visualization and abstraction of data and geometric accuracy, space and time.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.153

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.218
Teacher spread0.192 · 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