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Record W4415800155 · doi:10.1080/23273798.2025.2580970

Action and event-based lexical-semantic processing in Parkinson’s disease

2025· article· en· W4415800155 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

VenueLanguage Cognition and Neuroscience · 2025
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsWestern University
FundersNational Institutes of Health
KeywordsCognitionVerbAssociation (psychology)Action (physics)DiseaseExpressive Suppression

Abstract

fetched live from OpenAlex

We tested the hypothesis that Parkinson’s disease (PD) impairs verbs’ event structures and/or sensory-motor semantic features, as suggested by theories of grounded cognition. Nineteen participants with PD and 16 age-matched Controls produced verbs and used a Likert scale to rate verbs’ event-based association with instruments (e.g. fork – eating versus bathing) and locations (e.g. airport – waiting versus singing). When producing instrument-related verbs, PD participants responded slower and had a lower proportion of relevant responses than Controls. Yet PD participants showed a relatively intact ability to produce location-related verbs and to rate instrument- and location-related verbs. Greater motor disease primarily impacted instrument-related verb production. 4/19 PD participants had mild cognitive impairment (per Movement Disorders Society criteria), which affected both instrument- and location-related verb production and ratings. Overall, results were consistent with “weak” grounded cognition theories that propose that sensory-motor simulation may enrich action-semantic processing but is not strictly necessary for action-semantic 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.

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 score0.621
Threshold uncertainty score0.252

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 head0.043
GPT teacher head0.362
Teacher spread0.319 · 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