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Record W1995399481 · doi:10.1097/wnr.0b013e3283294061

Neural basis of sentence processing in which incoming words form a sentence

2009· article· en· W1995399481 on OpenAlexaff
Naho Ikuta, Motoaki Sugiura, Kentaro Inoue, Shigeru Sato, Kaoru Horie, Ryuta Kawashima

Bibliographic record

VenueNeuroreport · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsInstitute of Aging
FundersCenter for Strategic Research
KeywordsSentenceObject (grammar)PhraseSentence processingVerbNoun phrasePsychologyNounNatural language processingComputer scienceArtificial intelligenceAtomic sentenceSyntaxLinguistics

Abstract

fetched live from OpenAlex

This study examined the neural basis underlying the sequential involvement of sentence processing and determined the point at which the processing cost for an object-initial sentence was observed. We presented each phrase in a Japanese object-initial sentence to Japanese participants one by one using an event-related functional MRI technique and compared with our previous subject-initial experiment. We found that the left lingual gyrus was activated upon presentation of the first noun phrases, and the left inferior frontal gyrus upon presentation of the second noun phrases. The processing cost for an object-initial sentence was observed during verb recognition. Our results suggest that the syntactic complexity of an object-initial sentence is processed by the human brain upon verb recognition.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.304
Teacher spread0.273 · 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 designBench or experimental
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

Citations6
Published2009
Admission routes1
Has abstractyes

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