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Record W6925241721 · doi:10.17605/osf.io/8fwqu

Measuring brain activity when exposed to infant-directed speech: A meta-analysis

2023· other· en· W6925241721 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2023
Typeother
Languageen
FieldSocial Sciences
TopicScience and Science Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBrain activity and meditationCognitionNeuroimagingMental activityFunctional near-infrared spectroscopyHuman brainNeural activityPremovement neuronal activityBrain mapping

Abstract

fetched live from OpenAlex

In recent years, the number of infant studies using functional Near-Infrared Spectroscopy (fNIRS) has been steadily increasing. One of the main focuses in developmental cognitive neuroscience research is uncovering the brain correlates of speech processing. This is a meta-analysis, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, investigating the brain regions activated when presented with speech during infancy. Specifically, we will report on the field-wide result of whether the frontal and temporal lobes of both or either hemispheres are active when neonate to 12-month-old infants perceive auditory or audiovisual stimuli in studies employing fNIRS methodologies.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.6730.597

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 head0.140
GPT teacher head0.349
Teacher spread0.209 · 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