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Record W2143482469 · doi:10.1145/1342250.1342252

Safe 3D navigation

2008· article· en· W2143482469 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsAutodesk (Canada)
Fundersnot available
KeywordsComputer scienceUsabilityZoomHuman–computer interactionModalCADMultimediaArtificial intelligenceEngineering drawingEngineering

Abstract

fetched live from OpenAlex

Typical commercial 3D CAD tools provide modal tools such as pan, zoom, orbit, look, etc. to facilitate freeform navigation in a 3D scene. Mastering these navigation tools requires a significant amount of learning and even experienced computer users can find learning confusing and error-prone. To address this we have developed a concept called "Safe 3D Navigation" where we augment these modal tools with properties to reduce the occurance of confusing situations and improve the learning experience. In this paper we describe the major properties needed for safe navigation, the features we implemented to realize these properties, and usability tests on the effectiveness of these features. We conclude that indeed these properties do improve the learning experience for users that are new to 3D. Furthermore, many of the features we implemented for safe navigation are also very popular with experienced 3D users. As a result, these features have been integrated into six commercial 3D CAD applications and we recommend other application developers include these features to improve 3D navigation.

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 categoriesInsufficient payload (model declined to judge)
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 score0.922
Threshold uncertainty score1.000

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)0.0000.001

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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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

Quick stats

Citations69
Published2008
Admission routes1
Has abstractyes

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