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Record W2169675934 · doi:10.1017/s0317167100011057

Peripheral Trauma Induced Dystonia or Post-Traumatic Syndrome?

2011· review· en· W2169675934 on OpenAlexaffvenue
Hrishikesh Kumar, Mandar Jog

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2011
Typereview
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsDystoniaMedicinePeripheralPsychologyPhysical medicine and rehabilitationIntensive care medicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

The relationship between peripheral trauma and dystonia has been debated for more than a century but the issue still remains controversial. There are passionate supporters and detractors of the association and both the groups have their own arguments. This review aims to critically evaluate those arguments and presents current understanding of this association. In the process, the relevant case series and scientific papers exploring this subject have been discussed. Upon careful review of available literature coupled with their own experience, the authors believe that peripheral trauma can predispose to abnormal posturing of a body part after variable intervals. To call this posturing a "post-traumatic dystonia" might be premature and the term "post-traumatic syndrome" can be used instead. More work is needed to unravel the pathophysiology of this post-traumatic syndrome.

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)0.000
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.106
GPT teacher head0.328
Teacher spread0.221 · 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

Citations25
Published2011
Admission routes2
Has abstractyes

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