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Impulsiveness and executive functions in Parkinson’s disease

2019· dataset· en· W6939356182 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2019
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsImpulsivityExecutive functionsCognitionAssociation (psychology)CorrelationBarratt Impulsiveness ScaleCognitive impairmentDisease

Abstract

fetched live from OpenAlex

ABSTRACT Cognitive functions, such as impulsiveness and executive functions, are often impaired in Parkinson’s disease. Objective: to analyze the relationship between impulsiveness and executive functions (EF) in people with Parkinson’s disease (PD). Methods: a correlation study involving a sample of 50 patients with an established diagnosis of PD aged 40 years or older was conducted using the following instruments: Demographic Questionnaire, Montreal Cognitive Assessment Basic (MOCA-B), Barratt’s Impulsiveness Scale (BIS-11) and Frontal Assessment Battery (FAB). Results: Pearson’s correlation analysis indicated low associations (p<0.05) between the MOCA-B and BIS-11, with a value of -0.11, and between the FAB and BIS-11, with a value of -0.16. A significant correlation between the MOCA-B and FAB was found, with a value of 0.73. Conclusion: this study revealed an association between EF and other cognitive functions, but no association between impulsivity and EF in Parkinson’s disease.

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)0.004
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.024
GPT teacher head0.232
Teacher spread0.208 · 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
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

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