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Record W4313639341 · doi:10.1002/9781119898566.ch2

Metaverse: The New North Star

2023· other· en· W4313639341 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
Typeother
Languageen
FieldComputer Science
TopicMultimodal Machine Learning Applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMetaverseComputer scienceKey (lock)Human–computer interactionVirtual realityComputer security

Abstract

fetched live from OpenAlex

This chapter describes the origins of the Metaverse in Snow Crash in a more comprehensive fashion. It explains the key technologies enabling the Metaverse, including but not limited to the so-called non-fungible tokens (NFTs). Users of the Metaverse gain access to it through personal terminals that project a high-quality virtual reality display onto goggles or from low-quality public terminals that provide only a grainy black-and-white appearance. Sensing is the foundation of the Metaverse. Full coverage is essential to achieve global sensing and seamless connectivity, thereby providing unified experiences for users in the Metaverse. In the Metaverse, a comprehensive digital representation of the real world is created and maintained through digital twin technology. Blockchain is considered a key enabling technology for the Metaverse. NFTs have been widely in circulation only recently and already there are many that have become lost.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.260
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 science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.010

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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