MétaCan
Menu
Back to cohort
Record W1505428460 · doi:10.1109/gem.2014.7048124

Walking through sight: Seeing the ability to see, in a 3-D augmediated reality environment

2014· article· en· W1505428460 on OpenAlexaff
Ryan Janzen, Seyed Nima Yasrebi, Avishek Joey Bose, Arjun Subramanian, Steve Mann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSightSpace (punctuation)Computer scienceField (mathematics)Computer graphics (images)Mobile deviceFlux (metallurgy)Human–computer interactionAugmented realityField of viewWork (physics)Computer visionArtificial intelligencePhysicsOpticsMathematicsWorld Wide Web

Abstract

fetched live from OpenAlex

A 3-dimensional augmediated reality (AR) environment was designed, where users can physically walk through space, and by looking through AR glasses can see and interact with hidden veillance flux produced by cameras. Surveillance cameras, physically attached to a room, as well as handheld and body-worn cameras, each emit veillance flux and have a veillance field - a mathematical formulation of their capacity to see, as that capacity to see propagates through space. In this work, for the first time, we bring the mathematical veillance field into 3D augmediated reality, to "see sight".

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations12
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicAugmented Reality ApplicationsFrench-language works237,207