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Record W2346459493 · doi:10.1145/2851581.2892444

FlexStylus

2016· article· en· W2346459493 on OpenAlexafffund
Nicholas Fellion, Alexander Keith Eady, Audrey Girouard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsStylusFLEXComputer scienceAnalog deviceTactile sensorInput deviceProximity sensorComputer graphics (images)Computer visionArtificial intelligenceComputer hardwareAnalog signalDigital signal processingTelecommunications

Abstract

fetched live from OpenAlex

The FlexStylus is a prototype system that embeds sensors measuring analog flex input in a computer stylus. Through fiber optic sensing, the device detects both absolute extent and angle of flexion. The device was designed to allow these two channels of analog input, as well as derived parameters such as rate and relative motion, to augment the basic x/y functionality of a computer stylus. The goal of this augmentation is to improve a digital artist's ability to control their work through tactile manipulation, as well as expand the artist's range of expression and effects. We also introduce the use of flex input to create an additional pointing space, allowing for the execution of gestural drawing commands without moving the tip of the pen.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.999

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)0.0000.002

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 head0.227
Teacher spread0.219 · 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.

Study designBench or experimental
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

Citations6
Published2016
Admission routes2
Has abstractyes

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