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Record W4241382423 · doi:10.32920/ryerson.14653050.v1

Actibles: design and development of a new platform for active tangibles

2021· preprint· en· W4241382423 on OpenAlexaff
Brien G. East

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceSet (abstract data type)Embodied cognitionHuman–computer interactionSmartwatchSoftwareWearable computerEmbedded systemOperating systemArtificial intelligence

Abstract

fetched live from OpenAlex

In this thesis, we present a new kind of active tangible call an Actible. Actibles are an open source hardware/software platform for designing and implementing active tangibles for Tangible Embodied Interaction (TEI) applications. Web technologies and a smartwatch core are leveraged for ease of development, and enables the active tangibles to act coupled to a server, or act as their own server. This kind of connectivity enables the use of the Actibles independently or in combination with other devices and displays ubiquitously. We derived an expanded set of input and output interactions based on previous work on active tangibles, including tilting, shaking, neighboring, stacking, on-screen gestures, and integrated LED feedback. We describe the design and technical implementation of these interactions, and demonstrate it's use in a multitude of published example applications.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.768
Threshold uncertainty score0.821

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 science0.0010.001
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 head0.082
GPT teacher head0.308
Teacher spread0.226 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2021
Admission routes1
Has abstractyes

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