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Record W2890619558

Virtual Reality and Blockchain Technology in the Era of 5G: Disrupting Business and Society

2018· article· en· W2890619558 on OpenAlexaff
Aaron M. French, Marten Risius, J. P. Shim, Patrick S. Bordnick, Jeffrey Parsons, David Holtman

Bibliographic record

VenueJournal of the Association for Information Systems · 2018
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBlockchainVirtual realityAugmented realityComputer scienceImplementationBusiness modelMixed realitySet (abstract data type)TelecommunicationsComputer securityHuman–computer interactionBusinessSoftware engineering
DOInot available

Abstract

fetched live from OpenAlex

With the introduction of blockchain technology and advancements in the mobile infrastructure with 5G networks, virtual reality is resurfacing from previously discussed theoretical developments to actual implementations that are set to disrupt business and society alike. The past few years have shown an increase virtual reality equipment manufacturing and technical capabilities. With high speed networks capable of providing ubiquitous access, virtual and augmented reality platforms being developed on distributed blockchain networks, new societal transformations are ready to take place. This panel will address the technological foundation driving new trends and discuss their impacts on business and society.

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)0.003
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0080.014
Open science0.0000.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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 designTheoretical or conceptual
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

Citations2
Published2018
Admission routes1
Has abstractyes

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