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Record W2798340833 · doi:10.1145/3170427.3186477

GridDrones

2018· article· en· W2798340833 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsQueen's University
Fundersnot available
KeywordsVoxelMorphingComputer scienceGridRendering (computer graphics)Computer graphics (images)Cube (algebra)Artificial intelligenceComputer visionComputational scienceGeometryMathematics

Abstract

fetched live from OpenAlex

We present GridDrones, a self-levitating programmable matter platform that can be used for representing 2.5D 15 voxel grid relief maps with capabilities of rendering overhangs and 3D spatial transformations. GridDrones consists of 15 cube-shaped nanocopters that can be placed in a volumetric 1xnxn mid-air grid. Grid deformations can be applied interactively to this voxel lattice by first selecting a set of voxels using a 3D wand, then assigning a continuous topological relationship between voxel sets that determines how voxels move in relation to each other, then drawing out selected voxels from the lattice structure. Using this simple technique, it is possible to create overhanging structures that can be translated and oriented freely in 3D. Shape transformations can also be recorded to allow for simple physical shape morphing animations. This work extends previous work on selection and editing techniques for 3D user interfaces.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score1.000

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)0.0010.001

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 head0.009
GPT teacher head0.200
Teacher spread0.190 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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