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Record W2010363289 · doi:10.1016/j.acn.2007.04.008

Reaction time: An alternative method for assessing the effects of multiple sclerosis on information processing speed

2007· article· en· W2010363289 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArchives of Clinical Neuropsychology · 2007
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsOttawa HospitalCarleton University
Fundersnot available
KeywordsMultiple sclerosisInformation processingCognitionMedicineMeasure (data warehouse)Test (biology)AudiologyPsychologyComputer scienceCognitive psychologyPsychiatryData mining

Abstract

fetched live from OpenAlex

The ability of a newly developed measure of information processing to detect deficits in cognitive functioning associated with multiple sclerosis (MS) was investigated. The Computerized Tests of Information Processing (CTIP; Tombaugh, T., & Rees, L. (1999). Computerized Tests of Information Processing (CTIP). Unpublished test. Ottawa, Ontario, Canada: Carleton University) was administered to 60 clinically definite MS patients and 60 healthy controls. MS patients responded significantly slower than controls on the reaction time tests composing the CTIP. Moreover, as the CTIP tests became more difficult (i.e. as processing demands increased), the difference between the performances of the two groups progressively increased. These results suggest the CTIP is sensitive to the cognitive deficits observed in MS and that this measure has the potential to serve as a viable alternative to traditional measures of information processing speed currently in use with 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)0.002
metaresearch head score (Gemma)0.016
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 score0.951
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.142
GPT teacher head0.494
Teacher spread0.352 · 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