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Record W2291767237 · doi:10.1177/0891988715598231

Updating the Cognitive Performance Scale

2015· article· en· W2291767237 on OpenAlexaff
John N. Morris, Elizabeth Howard, Knight Steel, Christopher M. Perlman, Brant E. Fries, Vjenka Garms-Homolová, Jean‐Claude Henrard, John P. Hirdes, Gunnar Ljunggren, Len Gray, Katarzyna Szczerbińska

Bibliographic record

VenueJournal of Geriatric Psychiatry and Neurology · 2015
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCognitionScale (ratio)Effects of sleep deprivation on cognitive performanceDementiaPsychologyDistressMini–Mental State ExaminationMetric (unit)Activities of daily livingGerontologyCognitive declineClinical psychologyMedicinePsychiatryCognitive impairmentGeography

Abstract

fetched live from OpenAlex

This study presents the first update of the Cognitive Performance Scale (CPS) in 20 years. Its goals are 3-fold: extend category options; characterize how the new scale variant tracks with the Mini-Mental State Examination; and present a series of associative findings. Secondary analysis of data from 3733 older adults from 8 countries was completed. Examination of scale dimensions using older and new items was completed using a forward-entry stepwise regression. The revised scale was validated by examining the scale's distribution with a self-reported dementia diagnosis, functional problems, living status, and distress measures. Cognitive Performance Scale 2 extends the measurement metric from a range of 0 to 6 for the original CPS, to 0 to 8. Relating CPS2 to other measures of function, living status, and distress showed that changes in these external measures correspond with increased challenges in cognitive performance. Cognitive Performance Scale 2 enables repeated assessments, sensitive to detect changes particularly in early levels of cognitive decline.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.294
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations66
Published2015
Admission routes1
Has abstractyes

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Same venueJournal of Geriatric Psychiatry and NeurologySame topicDementia and Cognitive Impairment ResearchFrench-language works237,207