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Record W2043944566 · doi:10.1097/wnr.0b013e3280122718

Cerebral response to ‘voiceness’: a functional magnetic resonance imaging study

2007· article· en· W2043944566 on OpenAlexaff
Guylaine Bélizaire, Sarah Fillion-Bilodeau, Jean‐Pierre Chartrand, Caroline Bertrand-Gauvin, Pascal Belin

Bibliographic record

VenueNeuroreport · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsFunctional magnetic resonance imagingAuditory cortexStimulus (psychology)PsychologyMagnetoencephalographyAudiologySuperior temporal sulcusNeuroscienceSulcusCognitive psychologyElectroencephalographyMedicine

Abstract

fetched live from OpenAlex

We evaluated the response of the voice-selective areas of the auditory cortex to sound 'voiceness', that is, the degree to which an auditory stimulus resembles human voice. Normal participants were scanned using event-related functional magnetic resonance imaging while passively listening to stimuli drawn from a 'voiceness' continuum generated via auditory morphing between sounds of voice and sounds of musical instruments. The voice-selective areas of the left and right superior temporal sulcus did not show the expected relation between 'voiceness' and size effect. Instead, superior temporal sulcus activity seemed mostly driven by sound naturalness, with largest activity differences observed for the intermediate, voice-instrument hybrid stimuli.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.306
Teacher spread0.262 · 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

Citations24
Published2007
Admission routes1
Has abstractyes

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