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Record W2004074815 · doi:10.1207/s15324826an0702_6

Short-Form Prediction of WAIS-R Scores in a Sample of Individuals Diagnosed With Multiple Sclerosis

2000· article· en· W2004074815 on OpenAlex
Paul D. Mendella, Lorraine McFadden, Joe Regan, Lisa Medlock

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

VenueApplied Neuropsychology · 2000
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsWechsler Adult Intelligence ScalePsychologyContext (archaeology)Wechsler Preschool and Primary Scale of IntelligenceShort FormsClinical psychologyIntelligence quotientAudiologyDevelopmental psychologyWechsler Intelligence Scale for ChildrenCognitionPsychiatryMedicine

Abstract

fetched live from OpenAlex

A short form of the Wechsler Adult Intelligence Scale--Revised (WAIS-R) developed by Ward (WAIS-R/7 SF; 1990) was used to generate Verbal, Performance, and Full Scale IQ scores (VIQ, PIQ, and FSIQ, respectively) in 66 individuals diagnosed with multiple sclerosis (MS). Short-form scores were highly correlated with WAIS-R scores. However, the short-form VIQ and PIQ, but not FSIQ, scores differed significantly from corresponding WAIS-R scores. WAIS-R/7 SF VIQ, PIQ, and FSIQ scores fell within 5, 9, and 6 absolute error points, respectively, of corresponding WAIS-R IQ scores in 95% of cases. Classification of IQ scores into ranges (e.g., average, high average, etc.) based on the scheme outlined by Wechsler (1981) was consistent between WAIS-R/7 SF and WAIS-R scores in 81.8% (for VIQ), 74.8% (for PIQ), and 89.4% (for FSIQ) of cases. These findings are discussed within the context of using the WAIS-R/7 SF in the assessment of MS patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.072
GPT teacher head0.301
Teacher spread0.229 · 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