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Record W2998908810 · doi:10.1145/3347122.3371379

Curious Creatures

2019· article· en· W2998908810 on OpenAlexafffund
Sarah C. Vollmer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsYork University
FundersCanada First Research Excellence FundOntario Ministry of Research, Innovation and Science
KeywordsParallelsCreaturesProcess (computing)Human–computer interactionCuriosityAgency (philosophy)Computer scienceVirtual realityAnticipation (artificial intelligence)Conceptual frameworkEngineeringPsychologySociologyNatural (archaeology)Artificial intelligence

Abstract

fetched live from OpenAlex

The "Curious Creatures" project is an exploratory Research-Creation journey. Here, Digital Media practices in Virtual reality are developed through an ongoing and evolving methodology. Sensorial engagement and embodiment practices are explored through practical exposure and theoretical study. Interactions between a user and their (VR) environment (as both agents of design and agents of use during the creation process) mirror intellectual and emotional decisions faced throughout the ongoing construction process. Through the study of and participation in the creative process, human agency is tested through these human-computer interactions where virtual environments are constructed with the anticipation of controlling the user's actions. Parallels are drawn to existing art, conceptual frameworks, engineering practices, and technology that inspire this curiosity driven exploration.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0050.018
Scholarly communication0.0090.009
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.003

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 head0.004
GPT teacher head0.228
Teacher spread0.224 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes2
Has abstractyes

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