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Record W2092547575 · doi:10.1177/155005941004100410

EEG Analysis of Male to Female Transsexuals: Discriminant Function and Source Analysis

2010· article· en· W2092547575 on OpenAlexaff
Pierre Flor-Henry

Bibliographic record

VenueClinical EEG and Neuroscience · 2010
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
Fundersnot available
KeywordsSinistral and dextralTranssexualDiscriminant function analysisLinear discriminant analysisMale to femalePsychologyLateralization of brain functionElectroencephalographyAudiologyMedicineBiologyPsychiatryInternal medicineStatisticsTransgenderEpidemiologyMathematics

Abstract

fetched live from OpenAlex

A small series of consecutive, unmedicated male to female transsexuals were studied before hormonal treatment and prior to reassignment surgery. Quantitative EEG and LORETA source localization in the Eyes Open and Eyes Closed conditions were carried out, and they were compared to sinistral/ambilateral male and female controls, as the transsexual group was overwhelmingly sinistral. Discriminant function analysis and source localization showed that the transsexual group was similar to female heterosexual controls, with increased sources in the right hemisphere in the fast frequencies.

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 score0.002
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.374
Teacher spread0.299 · 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

Citations13
Published2010
Admission routes1
Has abstractyes

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