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Record W2137864660 · doi:10.1145/2556288.2557130

Consumed endurance

2014· article· en· W2137864660 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
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMetric (unit)Perceived exertionComputer scienceExertion3d printedTracking (education)SimulationHuman–computer interactionEngineeringPhysical therapyMedicinePsychologyBiomedical engineering

Abstract

fetched live from OpenAlex

Mid-air interactions are prone to fatigue and lead to a feeling of heaviness in the upper limbs, a condition casually termed as the gorilla-arm effect. Designers have often associated limitations of their mid-air interactions with arm fatigue, but do not possess a quantitative method to assess and therefore mitigate it. In this paper we propose a novel metric, Consumed Endurance (CE), derived from the biomechanical structure of the upper arm and aimed at characterizing the gorilla-arm effect. We present a method to capture CE in a non-intrusive manner using an off-the-shelf camera-based skeleton tracking system, and demonstrate that CE correlates strongly with the Borg CR10 scale of perceived exertion. We show how designers can use CE as a complementary metric for evaluating existing and designing novel mid-air interactions, including tasks with repetitive input such as mid-air text-entry. Finally, we propose a series of guidelines for the design of fatigue-efficient mid-air 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
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)0.0010.002

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 head0.044
GPT teacher head0.288
Teacher spread0.245 · 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

Citations395
Published2014
Admission routes1
Has abstractyes

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