MétaCan
Menu
Back to cohort
Record W4390733444 · doi:10.36074/logos-22.12.2023.099

NEUROPSYCHOLOGICAL TESTING OF COGNITIVE IMPAIRMENTS IN PATIENTS WITH MULTIPLE SCLEROSIS

2023· article· en· W4390733444 on OpenAlexaboutno aff
Олександра Тесленко

Bibliographic record

VenueSCIENTIFIC PRACTICE: MODERN AND CLASSICAL RESEARCH METHODS · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMultiple sclerosisNeuropsychologyCognitionMontreal Cognitive AssessmentCognitive impairmentNeuropsychological testingPsychologyMedicineNeuropsychological assessmentPhysical medicine and rehabilitationAudiologyPsychiatry

Abstract

fetched live from OpenAlex

Cognitive dysfunction in patients with relapsing-remitting multiple sclerosis (RRMS) is quite common, in about 70% of cases. The cognitive functionality of patients with MS according to the standards is assessed using the SDMT and PASAT-3 tests. Currently, the data on the validity of the MoCA in the diagnosis of cognitive impairments in patients with MS are ambiguous [4], however, there is much data on the effectiveness of the MoCA in detecting cognitive dysfunction [1, 2, 3].

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)0.004
metaresearch head score (Gemma)0.064
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.064
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.397
GPT teacher head0.513
Teacher spread0.116 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueSCIENTIFIC PRACTICE: MODERN AND CLASSICAL RESEARCH METHODSSame topicNeurological Disorders and TreatmentsFrench-language works237,207