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Record W2742775421

An evaluation of sensory and semantic contributions to imitation in individuals with Parkinson's disease

2010· article· en· W2742775421 on OpenAlexaff
Lauren Kielstra, Quincy J. Almeida, Éric Roy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsWilfrid Laurier UniversityUniversity of Waterloo
Fundersnot available
KeywordsGestureImitationApraxiaPsychologyCognitive psychologyParkinson's diseaseSet (abstract data type)Semantics (computer science)DiseaseNeuroscienceMedicineAphasiaComputer scienceArtificial intelligencePathology
DOInot available

Abstract

fetched live from OpenAlex

Higher order motor impairments are rarely investigated in movement disordered populations such as Parkinson's disease (PD). However, individuals with PD have been shown to elicit signs of apraxia with deficits in the spatial and temporal organization of gestures. According to the model of Roy et al (1991), it was hypothesized that both sensory and conceptual systems would contribute to the deficits in PD. The goal of the present study was to evaluate if individuals with PD would be less accurate during imitation of gestures without vision of their limbs, and/or less accurate during gestures that do not involve access to semantics. 48 PD and 16 healthy controls completed a set of imitation tasks involving meaningful and meaningless gestures performed with and without vision. Z-scores were computed for the PD relative to the controls. PD performed worse on meaningless gestures compared to meaningful gestures (p

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)0.001
metaresearch head score (Gemma)0.005
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.370
Teacher spread0.332 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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