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Record W2281429716 · doi:10.1145/2839462.2856339

POEME

2016· article· en· W2281429716 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMovement (music)Kinesthetic learningPoetrySpace (punctuation)AestheticsArtVisual artsComputer sciencePsychologyLiterature

Abstract

fetched live from OpenAlex

The interactive movement installation, POEME: A Poetry Engine explores the relationship between bodily, mechanical and digital interpretations of movement. The installation grew out of our design of POEME, a mobile website that responds to movement with poetic verse. While the POEME website can be used virtually anywhere, the installation anchors the interaction to a tangible space. We reference the choreographed routines of mass transit by giving participants a virtual ticket which grants them entrance to a private performance space. The participant's movement is conveyed outside of the space in the form of measurements and poetic verse created from words that relate to mechanical theories of movement. In order to understand the relationship between these interpretations and the bodily movement that powers POEME, the audience must experience the interaction for themselves. POEME builds off prior work in body-centric, experiential design. In contrast to systems that seek to identify individual features of movement, we instead attempt to characterize and respond to whole kinesthetic experiences through poetic verse.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
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)0.0000.001

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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

Citations25
Published2016
Admission routes2
Has abstractyes

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