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Ontology of Augmented Reality

2020· article· en· W3026311125 on OpenAlexaboutno aff
Vladimir Ignatyev

Bibliographic record

VenueDiscourse · 2020
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAugmented realitySocial realityInterpretation (philosophy)OntologySociologyVirtual realityMixed realityProcess (computing)EpistemologyMilgram experimentComputer scienceSocial sciencePsychologyHuman–computer interactionSocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

Introduction. The purpose of the paper is to justify the possibility of developing ontology of augmented reality as a special sphere of social space. A comparative analysis of approaches to the interpretation of reality in philosophy and theoretical sociology is carried out. The original provisions of the conceptual model of social reality and social actuality have been formulated. The concepts of actual and virtual social actions are introduced and analyzed. Methodology and sources. The main provisions of phenomenological sociology are used as the methodological basis of the study: A. Schutz's interpretation of social reality as a fragment of being translated into the world of intersubjective, and P. Berger and T. Luckmann's characterization of the reality of society as a process of its construction in practical activities. The features of augmented reality, revealed in the works of R. Azuma, P. Milgram, A. F. Kishino, H. Papagiannis, A. M. Larsen, S. A. Glazkova, O. N. Kislova and other researchers, are taken into account. Descriptions of the characteristics of augmented reality devices are derived from reports from research center heads: the descriptions of the characteristics of augmented reality devices are derived from reports from the heads of research centers involved in the development and implementation of digital technologies: universities in London, Tokio and Toronto, Hasso-Plattner Institute in Germany, Finnish company Senseg, company Disney Research, company High Fidelity, MIT self-assembly labs, MIT Media Lab Group, San Francisco-based Detour startup, Google and Microsoft etc. Results and discussion. The environment shaped by augmented reality is much more complex than it is in its immediate perception. It includes four spaces: 1) subject world, 2) the mental world and 3) the hybrid world as a symbiosis of real and imaginary worlds, or 4) symbiosis of real-world fragments – torn in space and time and combined with technology in devices that give the individual's ability to be present when observing their combined existence. Conclusion. Augmented reality complicates virtual reality, adding to its content in addition to fictional characteristics the content of practical actions. Augmented reality, using the virtual reality resource, becomes reality as the basis of practice. Augmented reality not only “begets” the world, but is in direct practical contact with it, thus becoming a special side of social reality.

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)0.002
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 score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.011
Scholarly communication0.0090.007
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.066
GPT teacher head0.341
Teacher spread0.275 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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