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Record W2010032120 · doi:10.1145/2800835.2801664

iMind

2015· article· en· W2010032120 on OpenAlexafffund
Isabel Pedersen, Pejman Mirza-Babaei, Nathan Gale

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsLakeridge Health
FundersiMindsSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsInteractivityBrain–computer interfaceComputer scienceHuman–computer interactionContext (archaeology)Dialogical selfMedia artsWearable computerInterface (matter)The artsDigital artKey (lock)MultimediaInteraction designInteractive artVisual artsArtPsychologyPerformance art

Abstract

fetched live from OpenAlex

The key contributions for this design paper are to showcase a working prototype of iMind that utilizes viewers' brainwave activity to personalize an aesthetic experience with the digitized art of Paul Klee. Digital humanities and arts methodologies were deliberately employed to conduct this design. iMind aims to broaden the exploratory outlook and application development of brain-computer interactivity [BCI] being used for creative experiences. iMind is a wearable tech application that explores BCI for the use in an art gallery context. iMind encourages the rediscovery of Paul Klee's artwork by promoting a dialogical experience amongst people, through a novel brain-computer interface.

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)0.003
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 score0.204
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2040.078

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 head0.046
GPT teacher head0.275
Teacher spread0.230 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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