MétaCan
Menu
Back to cohort
Record W2097553529 · doi:10.1525/mp.2008.26.2.157

Eye Movements and Music Reading: Where Do We Look Next?

2008· article· en· W2097553529 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.

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsReading (process)Eye movementCognitive psychologyPerceptionPsychologyCognitive scienceContext (archaeology)Contrast (vision)CognitionFocus (optics)Computer scienceArtificial intelligenceLinguisticsHistoryNeuroscience

Abstract

fetched live from OpenAlex

IN CONTRAST TO SIMILAR RESEARCH IN TEXT reading, research in the eye movements used to read music is relatively undeveloped. Though simpler measures such as the eye-hand span and perceptual span have been evaluated by numerous scholars, more complex phenomena such as context effects have yet to receive proper attention; this is largely the result of a lack of both focus on fine-grained structural properties (i.e., interval size, tonal-harmonic expectation) and a pool of hypotheses and paradigms informed by current models of music perception and cognition. To encourage further, more sophisticated research in eye movements and music reading, the present review discusses recent developments in the field and uses relevant conclusions to build a conceptual springboard for future research.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score1.000

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 studies0.0030.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.075
GPT teacher head0.333
Teacher spread0.258 · 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