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Record W2109648960 · doi:10.1145/2598784.2602795

The consumed endurance workbench

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

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.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0160.003

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

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 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

Citations16
Published2014
Admission routes1
Has abstractyes

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