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Record W2005830897 · doi:10.1002/mus.24207

Incat disability score: A critical analysis of its measurement properties

2014· article· en· W2005830897 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMuscle & Nerve · 2014
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhysical medicine and rehabilitationPhysical therapyQuality of life (healthcare)WeaknessReliability (semiconductor)MedicineChronic inflammatory demyelinating polyneuropathyPsychologySurgeryPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: The INCAT (Inflammatory Neuropathy Cause and Treatment) disability score is a measure of activity limitation. It is used frequently as a primary endpoint in inflammatory polyneuropathy clinical trials. A comprehensive critical analysis of its measurement properties has not been performed. METHODS: Critical analysis of measurement properties. RESULTS: The INCAT disability score was derived based on items from Guy's Neurological Disability Scale (GNDS), a disability measure intended for application in multiple sclerosis. Strengths of the INCAT score include evaluation of upper and lower limb dysfunction, ease of administration (feasibility), high face validity, and high reliability. Weaknesses of the scale include concerns about methodological quality of validation studies; failure to properly capture activity limitations due to proximal arm weakness, or fatigue; heavy individual item weighting; and poor sensitivity for detection of clinically important change. CONCLUSIONS: Although the INCAT scale has been an effective tool in inflammatory polyneuropathy studies, its limitations may warrant development of new scales.

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.

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)0.001
metaresearch head score (Gemma)0.008
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 score0.543
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
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 head0.213
GPT teacher head0.342
Teacher spread0.129 · 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