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Record W1490580326

Identification of tonic in popular and Baroque music in young and older adults using a dual keyboard apparatus

2000· article· en· W1490580326 on OpenAlexafffundvenue
Ian D. Toms, Annabel J. Cohen, M. J. Reina Lamothe

Bibliographic record

VenueCanadian acoustics · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Prince Edward Island
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Prince Edward IslandMcGill University
KeywordsTonalityRepetition (rhetorical device)Tonic (physiology)Dual (grammatical number)PsychologyMusicalComputer scienceSpeech recognitionCognitive psychologyAudiologyCommunicationArtNeuroscienceVisual artsLinguisticsMedicineLiterature
DOInot available

Abstract

fetched live from OpenAlex

A study was done to focus on the role of experience in tonality induction by comparing younger and older adults on contemporary popular and classical music excerpts using dual-keyboard technique. The dual-keyboard technique was found successful in revealing the ability of young and older listeners to systematically induce tonality regardless of their musical or keyboard experience. The procedure minimized memory and sensory constraints through repetition and provision of auditory feedback via the keyboard setup.

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)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.020
GPT teacher head0.248
Teacher spread0.228 · 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

Citations0
Published2000
Admission routes3
Has abstractyes

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