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Record W4281476646 · doi:10.1162/leon_a_02223

Reimagining Places, Reconstructing Histories: Augmented Reality Art and Heritage Apps as an Ultimate Display

2022· article· en· W4281476646 on OpenAlexaff
Liron Efrat

Bibliographic record

VenueLeonardo · 2022
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAugmented realityCultural heritageNarrativeVisual artsContext (archaeology)ArtAestheticsComputer scienceHuman–computer interactionHistoryArchaeologyLiterature

Abstract

fetched live from OpenAlex

Abstract This article employs Ivan Sutherland’s 1965 concept of the Ultimate Display to discuss the experience generated by augmented reality art and cultural heritage. Analyzing projects that reimagine or reconstruct reality, the author discusses the social impact and cultural workings of these apps. The article shows how such apps can facilitate kinesthetic performances that intervene in established cultural narratives and open a window to new social realities. In this context, the author also introduces her project CHAR, an online collection of AR art and cultural heritage apps, which illustrates how Sutherland’s vision has been materialized through the mapping of AR-reconstructed realities.

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 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)0.001
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: none
Teacher disagreement score0.833
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.018
GPT teacher head0.267
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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

Citations1
Published2022
Admission routes1
Has abstractyes

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