MétaCan
Menu
Back to cohort
Record W2147174242 · doi:10.1093/brain/awh323

Pathological study of spinal cord atrophy in multiple sclerosis suggests limited role of local lesions

2004· article· en· W2147174242 on OpenAlexaff
Nikos Evangelou

Bibliographic record

VenueBrain · 2004
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsAtrophySpinal cordMultiple sclerosisPathologyMedicinePathologicalLesionCordCentral nervous system diseaseCentral nervous systemDegenerative diseaseDiseaseInternal medicineSurgeryImmunology

Abstract

fetched live from OpenAlex

Imaging studies in multiple sclerosis have shown that spinal cord atrophy correlates with clinical disability. The pathological substrate of atrophy has not as yet been investigated adequately. In order to determine the cause of spinal cord atrophy in multiple sclerosis, five different sections of the spinal cord were examined histopathologically in 33 controls and 55 multiple sclerosis cases. In the multiple sclerosis cases in each section the total lesion load and the cross-sectional area of the cord were measured. Multiple regression models were estimated, controlling for sex, age, duration of the disease and location of the cord sections. The multiple sclerosis cords were found to be significantly smaller than the controls. The duration of the disease played the most important role in determining cord atrophy. The degree of atrophy varied in different parts of the cord. Individual lesions played a minor role in local atrophy. Our findings suggest that axonal degeneration, possibly caused by the cumulative number of lesions in the brain and cord, or an alternative atrophic process, is responsible for spinal cord atrophy in multiple sclerosis, rather than tissue loss within individual lesions.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.117
GPT teacher head0.341
Teacher spread0.223 · 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.

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

Citations153
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueBrainSame topicMultiple Sclerosis Research StudiesFrench-language works237,207