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Record W4387092583 · doi:10.1109/mce.2023.3319849

INTERBEING: On the Symbiosis Between INTERnet and Human BEING

2023· article· en· W4387092583 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Consumer Electronics Magazine · 2023
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceLeverage (statistics)MetaverseVirtuality (gaming)The InternetEmbodied cognitionVirtual realityWearable computerTechnoscienceHuman–computer interactionWorld Wide WebArtificial intelligenceSociologySocial science

Abstract

fetched live from OpenAlex

With the advent of the metaverse, the future 3D spatial Internet will be about being inside the Internet rather than simply looking at it from a 2D computer or smartphone screen. This article aims at exploring the sociality dimension, AI integration in eXtended meta-uni-omni-Verse, and stigmergy principles. It puts a particular focus on the unifying design of virtual, embodied, intelligent cross-reality environments, ranging from our proposed stigmergic Society 5.0 to Interbeing based on the symbiosis between Inter(net) and (human) being—a word that is not in the dictionary yet. In addition to tokenized digital twins, we leverage on hyperintelligent life-like digital organisms that symbiomimic biological superorganisms. In doing so, they lay the foundation for creating a future stigmergic virtual society that benefits from the convergence of digital evolution and biology as well as advanced eXtended Reality wearables for tapping into the entire reality-virtuality continuum of the metaverse's emerging virtual 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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.287
Teacher spread0.253 · 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