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Record W604299515 · doi:10.1017/cbo9781139207294

Magnetic Resonance Imaging in Movement Disorders

2013· book· en· W604299515 on OpenAlexaff
Paul Tuite

Bibliographic record

VenueCambridge University Press eBooks · 2013
Typebook
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsMovement disordersMagnetic resonance imagingDystoniaMedicineParkinson's diseasePsychologyFunctional magnetic resonance imagingPhysical medicine and rehabilitationEssential tremorNeuroscienceDiseaseRadiologyPathology

Abstract

fetched live from OpenAlex

Magnetic Resonance Imaging in Movement Disorders is the first book to focus in detail on MRI in a range of movement disorders. Since MRI was first employed in imaging Parkinson's disease, the number of imaging techniques and their application in diagnosis and management has extended widely. The book shows various imaging strategies ranging from functional, structural and chemical methods as they relate to both motor and non-motor aspects of Parkinson's disease and other conditions such as Huntington's disease and dystonia. Chapters on MRI in surgery and using MRI as a potential outcome measure in clinical trials show the clinical relevance of methods. Novel methods including DTI, tractography and resting case studies are described in detail. The book also summarises the relevance of fMRI to various aspects of movement disorders. Magnetic Resonance Imaging in Movement Disorders is essential reading for neurologists, radiologists and movement disorder specialists.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.061
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0610.049

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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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
GenreOther

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

Citations12
Published2013
Admission routes1
Has abstractyes

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