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Record W3021068506 · doi:10.1080/13546805.2020.1760812

The cognitive neuropsychiatry of Tourette syndrome

2020· review· en· W3021068506 on OpenAlexaff
Andrea E. Cavanna, Christos Ganos, Andreas Hartmann, Davide Martino, Tamara Pringsheim, Stefano Seri

Bibliographic record

VenueCognitive Neuropsychiatry · 2020
Typereview
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyTicsCognitionNeuropsychiatryNeurocognitiveTourette syndromeSocial cognitionClinical psychologyPsychiatryCognitive psychology

Abstract

fetched live from OpenAlex

Introduction: Converging evidence from both clinical and experimental studies has shown that Tourette syndrome (TS) is not a unitary condition, but a cluster of multiple phenotypes, which encompass both tics and specific behavioural and cognitive symptoms (mainly attention-deficit and hyperactivity disorder and obsessive-compulsive disorder).Methods: We conducted a narrative review of the recent literature on the cognitive neuropsychiatry of TS.Results: Although clinical research has shown that TS is not associated with cognitive deficits per se, the findings of recent studies have suggested the presence of subtle alterations in specific cognitive functions. A promising line of research on imitative behaviour could provide a common background for the alterations in executive control and social cognition observed in TS. Two different (but not mutually exclusive) neurocognitive theories have recently suggested that TS could originate from altered perception-action binding and social decision-making dysfunction, respectively.Conclusions: Since the presence of behavioural comorbidities influences individualised treatment approaches, it is likely that a more precise characterisation of TS phenotypes, including cognitive aspects, will result in improved levels of care for patients with tic disorders.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.334
Teacher spread0.311 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations23
Published2020
Admission routes1
Has abstractyes

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