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Record W2023570449 · doi:10.1145/2659766.2659769

Ethereal planes

2014· article· en· W2023570449 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceVariety (cybernetics)WorkspaceHuman–computer interactionSet (abstract data type)Window (computing)CockpitWorld Wide WebEngineeringRobotArtificial intelligence

Abstract

fetched live from OpenAlex

Information spaces are virtual workspaces that help us manage information by mapping it to the physical environment. This widely influential concept has been interpreted in a variety of forms, often in conjunction with mixed reality. We present Ethereal Planes, a design framework that ties together many existing variations of 2D information spaces. Ethereal Planes is aimed at assisting the design of user interfaces for next-generation technologies such as head-worn displays. From an extensive literature review, we encapsulated the common attributes of existing novel designs in seven design dimensions. Mapping the reviewed designs to the framework dimensions reveals a set of common usage patterns. We discuss how the Ethereal Planes framework can be methodically applied to help inspire new designs. We provide a concrete example of the framework's utility during the design of the Personal Cockpit, a window management system for head-worn displays.

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: none
Teacher disagreement score0.988
Threshold uncertainty score0.938

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.005
GPT teacher head0.216
Teacher spread0.210 · 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

Citations102
Published2014
Admission routes2
Has abstractyes

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