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Record W1994049044 · doi:10.1179/174313208x297030

Foot control in incomplete SCI: distinction between paresis and dexterity

2008· article· en· W1994049044 on OpenAlexaff
Brigitte Wirth, Hubertus J. A. van Hedel, Armin Curt

Bibliographic record

VenueNeurological Research · 2008
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhysical medicine and rehabilitationParesisFoot (prosody)PsychologyMedicineSurgeryPhilosophy

Abstract

fetched live from OpenAlex

OBJECTIVE: To complement the clinical assessment of motor impairment after incomplete spinal cord injury (iSCI) by introducing a test that reliably distinguishes between muscle weakness (paresis) and impairment of dexterity in a simple foot motor task. METHODS: Auditory-paced ankle dorsi- and plantarflexion, in a supine position, was studied in 30 controls (to establish control values and to test reliability) and in 16 iSCI patients (test validation). The subjects were instructed to initiate dorsi- and plantarflexion as accurately in timing and with the largest range of motion (ROM) possible. For each frequency, accuracy of timing, ROM, peak velocity of dorsi- and plantarflexion and a time quotient for changing from dorsi- to plantarflexion and vice versa were determined. In iSCI subjects, these parameters were related to clinical measures of paresis, spasticity and proprioception. RESULTS: The test parameters showed good to very good reliability. The iSCI subjects were able to follow the target frequency with high accuracy, while ROM and peak velocity for dorsi- and plantarflexion were significantly reduced. Furthermore, there was a strong correlation between ROM/peak velocities and motor scores within the iSCI patients. DISCUSSION: Repetitive foot dorsi- and plantarflexion enables a distinction to be made between muscle weakness and reduced dexterity as the underlying cause of affected foot control. This distinction between and quantification of these two movement components complements the existing clinical examination, and in follow-up works, the recovery of these components may provide further insight into the mechanisms underlying motor function improvement after iSCI.

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)0.003
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.326
GPT teacher head0.466
Teacher spread0.141 · 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

Citations19
Published2008
Admission routes1
Has abstractyes

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