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Record W2049547708 · doi:10.1109/icsens.2013.6688614

MRI-compatible optically-sensed cello

2013· article· en· W2049547708 on OpenAlexafffund
Avrum Hollinger, Marcelo M. Wanderley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
FundersCentre for Interdisciplinary Research in Music Media and Technology
KeywordsCelloScannerMicrophoneAcousticsComputer scienceOpticsRotation (mathematics)PhysicsLoudspeakerArtificial intelligence

Abstract

fetched live from OpenAlex

An opto-acoustic cello has been designed to investigate the neural correlates of cello performance using functional magnetic resonance imaging (MRI). Through the design of specialized optical sensors, for the first time, we are able to synchronously capture a cellist's acoustic performance and musical gestures within the MRI scanner. The electromagnetic constraints and confined space of the scanner were overcome through the design of a minimalist composite cello body, a bridge and transparent fingerboard embedded with optical fibers, and a sensorized shortened bow. Using an array of fibers embedded in the fingerboard, we captured finger position and vibrato. Bending losses in fibers placed between the bridge and string, as a contact microphone, allowed us to capture the acoustic performance. Bow displacement was acquired separately using an optical flow sensor and by measuring Faraday rotation in an optical crystal within the magnetic field of the scanner.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.037
GPT teacher head0.263
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations8
Published2013
Admission routes2
Has abstractyes

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