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Record W1592491412 · doi:10.1111/pme.12518

Mechanisms Underlying Chronic Whiplash: Contributions from an Incomplete Spinal Cord Injury?

2014· article· en· W1592491412 on OpenAlexaff
James M. Elliott, Julius P. A. Dewald, T. George Hornby, David M. Walton, Todd B. Parrish

Bibliographic record

VenuePain Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsWestern University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Center for Research Resources
KeywordsMedicineWhiplashSpinal cord injuryPhysical medicine and rehabilitationSpinal cordMagnetic resonance imagingPhysical therapyWhiplash injuryRehabilitationPlantar flexionPoison controlAnatomyRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the association between findings on advanced, but available, magnetic resonance imaging (MRI) sequences of the cervical spinal cord and muscular system, in tandem with biomechanical measures of maximum volitional plantar flexion torques as a proxy for a mild incomplete spinal cord injury. DESIGN: Observational case series. SETTING: University research laboratory. SUBJECTS: Three patients with chronic whiplash and one patient with history of whiplash injury but no current symptoms. METHODS: We measured lower extremity muscle fat, morphological changes in descending spinal cord pathways with advanced MRI applications and maximal activation of the plantar flexors. RESULTS: Larger magnitudes of lower extremity muscle fat corresponded to altered spinal cord anatomy and reductions in the ability to maximally activate plantar flexor torques in the three subjects with chronic whiplash. Such findings were not present in the recovered participant. CONCLUSIONS: The potential value of MRI to quantify neuromuscular degeneration in chronic whiplash is recognized. Larger scaled prospective studies are warranted before stronger conclusions can be drawn.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.041
GPT teacher head0.366
Teacher spread0.325 · 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 teacher head, not a consensus.

Study designOther design
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

Citations27
Published2014
Admission routes1
Has abstractyes

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