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A Protocol for Cross‐Cultural Research on the Acquisition of Singing

2009· article· en· W2096933933 on OpenAlexafffund
Annabel J. Cohen, Vickie Armstrong, Marsha S. Lannan, Jenna D. Coady

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Prince Edward Island
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSingingProtocol (science)The InternetComputer scienceMultimediaWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

As part of a major collaborative research initiative, Advancing Interdisciplinary Research in Singing (AIRS), we developed a protocol for obtaining audiovisual information reflecting aspects of the ability to sing. We also developed a digital library prototype, the Children's International Media Exchange for Singing (CHIMES), to index and store the data for access through the Internet by researchers worldwide. The protocol was piloted at five monthly intervals with 20 individuals (children 3, 5, and 7 years of age and adults differing in vocal training level), validating its feasibility in Western culture and producing rich data amenable to numerous levels and kinds of analysis.

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)0.045
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.140
Threshold uncertainty score0.469

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.039
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0060.003
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.1400.042

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 head0.470
GPT teacher head0.522
Teacher spread0.052 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations15
Published2009
Admission routes2
Has abstractyes

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