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Record W2136792941 · doi:10.1525/mp.2008.25.4.331

ON-LINE IDENTIFICATION OF CONGENITAL AMUSIA

2008· article· en· W2136792941 on OpenAlexaff
Isabelle Peretz, Nathalie Gosselin, Barbara Tillmann, Lola L. Cuddy, Benoît Gagnon, Christopher G. Trimmer, Sébastien Rioux Paquette, Bernard Bouchard

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité de MontréalQueen's UniversityInternational Laboratory for Brain, Music and Sound Research
Fundersnot available
KeywordsPsychologyAudiologyIdentification (biology)PopulationDevelopmental psychologyCognitive psychologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

RECENTLY, WE POINTED OUT THAT A SMALL number of individuals fail to acquire basic musical abilities, and that these deficiencies might have neuronal and genetic underpinnings. Such a musical disorder is now termed "congenital amusia," an umbrella term for lifelong musical disabilities that cannot be attributed to mental retardation, deafness, or lack of exposure. Congenital amusia is a condition that is estimated to affect 4% of the general population. Despite this relatively high prevalence, cases of congenital amusia have been difficult to identify.We present here a novel on-line test that can be used to identify such cases in 15 minutes, provided that the cohort of the participant is taken into account. The results also confirm that congenital amusia is typically expressed by a deficit in perceiving musical pitch but not musical time.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.092
GPT teacher head0.355
Teacher spread0.263 · 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

Citations121
Published2008
Admission routes1
Has abstractyes

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