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Record W2148014680 · doi:10.1093/brain/awh167

Posterior fossa lesion volume and slowed information processing in multiple sclerosis

2004· article· en· W2148014680 on OpenAlexafffund
Cate J. Archibald, Xiaoli Wei, James N. Scott, Christopher Wallace, Yuchen Zhang, Luanne M. Metz, J. Ross Mitchell

Bibliographic record

VenueBrain · 2004
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of TorontoUniversity of CalgaryFoothills Medical Centre
FundersFondation pour la Recherche MédicaleMultiple Sclerosis SocietyMultiple Sclerosis Society of Canada
KeywordsMultiple sclerosisLesionCognitionMedicineMagnetic resonance imagingPathologicalPsychologyNeuroscienceAudiologyPathologyRadiologyPsychiatry

Abstract

fetched live from OpenAlex

The relationship between performance on information processing efficiency measures and MRI-derived lesion volume including global and regional T2 and T1 lesion volumes was investigated in 20 patients with relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS). Processing speed, as measured by the Sternberg Memory Scanning Test, was significantly correlated with posterior fossa lesion volume and slowed reaction time in seven out of eight patients (six out of seven with SPMS) with any lesion volume in the posterior fossa suggesting a 'threshold effect'. Processing capacity as measured by the Salthouse Keeping Track Test was not significantly correlated with the MRI measures. Cognitive performance did not correlate with Expanded Disability Status Scale score, depression or fatigue, and patients performed within normal limits on tests of attention/concentration ability. The significant relationship between posterior fossa lesion volume and memory scanning speed in this study suggests that pathological damage in the posterior fossa may contribute to slowed cognitive processing and may be an important direction for future studies of cognitive function in multiple sclerosis. Lack of correlation of cognitive measures with the other MRI measures may be due to low lesion volume relative to other studies, sample composition, and limited pathological specificity of the MRI measures.

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)0.001
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 score0.857
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.076
GPT teacher head0.302
Teacher spread0.227 · 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

Citations40
Published2004
Admission routes2
Has abstractyes

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