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Record W2092076993 · doi:10.1080/00207450212015

BILINGUAL MEN BUT NOT WOMEN DISPLAY LESS LEFT EAR BUT NOT RIGHT EAR ACCURACY DURING DICHOTIC LISTENING COMPARED TO MONOLINGUALS

2002· article· en· W2092076993 on OpenAlexaff
Michael A. Persinger, G. CHELLEW-BELANGER, S. G. Tiller

Bibliographic record

VenueInternational Journal of Neuroscience · 2002
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsLaurentian University
Fundersnot available
KeywordsDichotic listeningAudiologyActive listeningLeft and rightPsychologyLateralityMedicineCommunication

Abstract

fetched live from OpenAlex

Kimura Recurring Figures were presented after the priming trial to the upper or lower, left or right, tachistoscopic fields while monopolar electroencephalographic activity was measured over the left and right parietal, occipital, and temporal lobes for 9 men and 9 women. The relative proportions of alpha rhythms during the 2 sec after each of 64 presentations were employed as the primary measure. The powerful asymmetry in electroencephalographic activity, manifested as a paucity of alpha activity over the right temporal lobe compared to the left temporal lobe, was not observed for the parietal or occipital regions. There was conspicuously more relative activity over the parietal and occipital lobes, but not over the temporal lobes, during presentations of the familiar figures compared to the unfamiliar figures. Several interactions--explaining more than 25% of the variance--between gender, left and right hemispheric EEG activity, and visual quadrants were consistent with lateralization of function and gender differences in functional brain organization.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

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)0.0090.001

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 head0.066
GPT teacher head0.359
Teacher spread0.293 · 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

Citations17
Published2002
Admission routes1
Has abstractyes

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