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Record W2018520140 · doi:10.1196/annals.1284.019

Cortical Correlates of Acquired Deafness to Dissonance

2003· article· en· W2018520140 on OpenAlexaff
Elvira Brattico, Mari Tervaniemi, Vesa Välimäki, Titia L. van Zuijen, Isabelle Peretz

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2003
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsConsonance and dissonanceCognitive dissonancePsychologyAuditory cortexConsonantNeuroscienceAudiologyMusicalCognitive psychologyPhenomenonCortex (anatomy)LinguisticsMedicineSocial psychologyAcousticsPhysicsArtPhilosophy

Abstract

fetched live from OpenAlex

Patient I.R., who had bilateral lesions in the auditory cortex but intact hearing, did not distinguish dissonant from consonant musical excerpts in behavioral testing. We additionally found that the electrical brain responses did not differentiate musical intervals in terms of their dissonance/consonance, consistent with the idea that this phenomenon depends on the integrity of cortical functions.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.138
GPT teacher head0.363
Teacher spread0.225 · 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 designObservational
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

Citations10
Published2003
Admission routes1
Has abstractyes

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