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Record W2017439228 · doi:10.1145/958432.958489

Demo

2003· article· en· W2017439228 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
TopicAugmented Reality Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHaptic technologyComputer scienceHuman–computer interactionVirtual realitySet (abstract data type)GraphicsVirtual machineComputer graphicsMultimediaInput deviceSimulationComputer graphics (images)Operating system

Abstract

fetched live from OpenAlex

This demonstration presents the current state of an on-going team project at Simon Fraser University in developing a virtual environment for helping to train surgeons in performing laparoscopic surgery. In collaboration with surgeons, an initial set of training procedures has been developed. Our goal has been to develop procedures in each of several general categories, such as basic hand-eye coordination, single-handed and bi-manual approaches and dexterous manipulation. The environment is based on an effective data structure that offers fast graphics and physically based modeling of both rigid and deformable objects. In addition, the environment supports both 3D and 5D input devices and devices generating haptic feedback. The demonstration allows users to interact with a scene using a haptic device.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score0.485

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 head0.014
GPT teacher head0.238
Teacher spread0.224 · 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

Citations10
Published2003
Admission routes1
Has abstractyes

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