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Record W2394570920 · doi:10.1145/2858036.2858519

BitDrones

2016· article· en· W2394570920 on OpenAlexafffund
Antônio Tadeu A. Gomes, Calvin Rubens, Sean Braley, Roel Vertegaal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTouchscreenComputer scienceComputer graphics (images)Interface (matter)LevitationHuman–computer interactionUser interfaceAugmented realityEngineeringOperating systemElectrical engineering

Abstract

fetched live from OpenAlex

We present BitDrones, a toolbox for building interactive real reality 3D displays that use nano-quadcopters as self-levitating tangible building blocks. Our prototype is a first step towards interactive self-levitating programmable matter, in which the user interface is represented using Catomic structures. We discuss three types of BitDrones: PixelDrones, equipped with an RGB LED and a small OLED display; ShapeDrones, augmented with an acrylic mesh spun over a 3D printed frame in a larger geometric shape; and DisplayDrones, fitted with a thin-film 720p touchscreen. We present a number of unimanual and bimanual input techniques, including touch, drag, throw and resize of individual drones and compound models, as well as user interface elements such as self-levitating cone trees, 3D canvases and alert boxes. We describe application scenarios and depict future directions towards creating high-resolution self-levitating programmable matter.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.104
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1040.026

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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations110
Published2016
Admission routes2
Has abstractyes

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