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Record W2397820364

Sense/Stage - Low Cost, Open Source Wireless Sensor Infrastructure For Live Performance And Interactive, Real-Time Environments

2010· article· en· W2397820364 on OpenAlexaff
Marije A. J. Baalman, Vincent De Belleval, Joseph Malloch, Joseph Thibodeau

Bibliographic record

VenueThe Journal of the Abraham Lincoln Association · 2010
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill UniversityConcordia University
Fundersnot available
KeywordsFirmwareComputer scienceWireless sensor networkWirelessWireless networkSoftwareMultimediaTelecommunicationsComputer networkOperating system
DOInot available

Abstract

fetched live from OpenAlex

SenseStage is a research-creation project to develop a wireless sensor network infrastructure for live performance and interactive, real-time environments. The project is motivated by the economic and technical constraints of live performance contexts and the lack of existing tools for artistic work with wireless sensing platforms. The development is situated within professional artistic contexts and tested in real world scenarios. In this paper we discuss our choice of wireless platform, the design of the hardware and firmware, battery options, and an evaluation of the data transmission quality within the wireless network. Additionally, software integration of the wireless platform with popular media programming environments is addressed, as well as evaluation and dissemination of the technology through workshops. Finally, we elaborate on the application of the hardware and software infrastructure in professional artistic projects: two dance performances, two media projects involving environmental data and an interactive, multi-sensory installation.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.231
Teacher spread0.226 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2010
Admission routes1
Has abstractyes

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