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Record W2109648960 · doi:10.1145/2598784.2602795

The consumed endurance workbench

2014· article· en· W2109648960 on OpenAlex
Juan David Hincapié-Ramos, Xiang Guo, Pourang Irani

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
FieldComputer Science
TopicHand Gesture Recognition Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsWorkbenchMetric (unit)Computer scienceTracking (education)Human–computer interactionSimulationEngineering drawingArtificial intelligenceEngineeringVisualization

Abstract

fetched live from OpenAlex

Consumed Endurance (CE) [8] is a metric that captures the degree of arm fatigue during mid-air interactions. Research has shown that CE can assist with the design of new and minimally fatiguing gestural interfaces. We introduce the Consumed Endurance Workbench, an open source application that calculates CE in real time using an off-the-shelf skeleton tracking system. The CE Workbench tracks a person's arm as it is moved in mid-air, determining the forces involved and calculating CE over the length of the interaction. Our demonstration focuses on how to use the CE Workbench to evaluate alternative mid-air gesture designs, how to integrate the CE Workbench with existing applications, and how to prepare the CE data for statistical analysis. We also demonstrate a mid-air text-entry layout, SEATO, which we created taking CE as the main design factor.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.830

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 science0.0010.000
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 head0.010
GPT teacher head0.216
Teacher spread0.207 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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