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Record W2146454608 · doi:10.1097/wnr.0b013e32832000f8

Similarities in neural activations of face and Chinese character discrimination

2009· article· en· W2146454608 on OpenAlexaff
Jiangang Liu, Jie Tian, Jun Li, Qiyong Gong, Kang Lee

Bibliographic record

VenueNeuroreport · 2009
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFace (sociological concept)PsychologyChinese charactersVisual processingCharacter (mathematics)Fusiform face areaSymbol (formal)Face perceptionCommunicationVisual cortexCognitive psychologyNeurosciencePerceptionLinguisticsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This study compared Chinese participants' visual discrimination of Chinese faces with that of Chinese characters, which are highly similar to faces on a variety of dimensions. Both Chinese faces and characters activated the bilateral middle fusiform with high levels of correlations. These findings suggest that although the expertise systems for faces and written symbols are known to be anatomically differentiated at the later stages of processing to serve face processing or written-symbol-specific processing purposes, they may share similar neural structures in the ventral occipitotemporal cortex at the stages of visual processing.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.940
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.048
GPT teacher head0.316
Teacher spread0.268 · 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 teacher head, 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

Citations27
Published2009
Admission routes1
Has abstractyes

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