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Record W1998043530 · doi:10.1258/1357633001935437

The Cave-let: A low-cost projective immersive display

2000· article· en· W1998043530 on OpenAlexaff
Mark Green, Lloyd T. White

Bibliographic record

VenueJournal of Telemedicine and Telecare · 2000
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer sciencePID controllerRange (aeronautics)VisualizationHuman–computer interactionArtificial intelligenceEngineeringAerospace engineeringTemperature controlControl engineering

Abstract

fetched live from OpenAlex

This paper describes the design and implementation of a low-cost projective immersive display (PID), called the Cave-let. A PID immerses the user in a computer-generated three-dimensional environment that responds to the user's movements. Current devices of this nature are very expensive, so that fewer than 100 units have been installed around the world. A low-cost PID will enable a wide range of applications in areas such as telehealth, visualization, education and collaborative systems. To produce a low-cost PID, we identified the components of the design that represented the major costs. These were then redesigned with the aim of reducing cost as much as possible while preserving most of the functionality. The resulting device is suitable for a wide range of applications and is an order of magnitude less expensive than similar devices.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations4
Published2000
Admission routes1
Has abstractyes

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