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Record W2006982329 · doi:10.5555/2386275.2386286

Parts, image, and sketch based 3D modeling method

2006· article· en· W2006982329 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

VenueSketch Based Interfaces and Modeling · 2006
Typearticle
Languageen
FieldComputer Science
TopicComputer Graphics and Visualization Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMorphingSketchComputer science3D modelingSoftwareDomain (mathematical analysis)Geometric modelingSolid modeling3d modelHuman–computer interactionInterface (matter)Artificial intelligenceTransformation (genetics)Computer graphics (images)Computer visionProgramming languageEngineeringAlgorithm

Abstract

fetched live from OpenAlex

Despite their many benefits, challenges exist in the creation of 3D models, particularly for individual not currently skilled with 3D modeling software. To address this, we explore the creation of 3D modeling software for non-domain experts that uses a hierarchical parts database of generic 3D models, and deforms models into specific related target objects using image guided 3D model morphing. A human-in-the-loop sketching interface supports image registration and constrains our geometrical transformation to support real time morphing of generic models into accurate representations of new objects for which users wish a 3D model. Applying the application to the study of insects in biology, we find that the application supports the creation of realistic 3D models, and that the application is of value to educators and researchers in entomology.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.583
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.028
GPT teacher head0.315
Teacher spread0.286 · 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