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Record W4394825444 · doi:10.1109/vr58804.2024.00012

The Laval Phenomenon: A Deep Dive into France’s VR Capital

2024· article· en· W4394825444 on OpenAlexaboutno aff
Simon Richir

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGlobeVirtual realityPhenomenonAugmented realityMixed realityEvent (particle physics)Human–computer interactionCenter (category theory)Computer sciencePsychologyPhysics

Abstract

fetched live from OpenAlex

This 30-minute conference delves into the remarkable story of Laval, a small French town that emerged as a global center for research and development in virtual reality (VR) and augmented reality (AR). Since the inception of Laval Virtual in 1999, this event has been pivotal in bringing together pioneers, researchers, entrepreneurs, and enthusiasts of interactive and immersive technologies from around the globe.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0140.011
Scholarly communication0.0190.006
Open science0.0010.006
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0140.001

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 head0.005
GPT teacher head0.237
Teacher spread0.231 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same topicAugmented Reality ApplicationsFrench-language works237,207