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Record W2738458940 · doi:10.1159/000478008

Assessing Capacity in the Elderly: Comparing the MoCA with a Novel Computerized Battery of Executive Function

2017· article· en· W2738458940 on OpenAlex
Megan Brenkel, Kenneth I. Shulman, Elias Hazan, Nathan Herrmann, Adrian M. Owen

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

VenueDementia and Geriatric Cognitive Disorders Extra · 2017
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsWestern UniversitySunnybrook Hospital
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionExecutive functionsPsychologyGerontologyMedicineCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Clinicians are increasingly being asked to provide their opinion on the decision-making capacity of older adults, while validated and widely available tools are lacking. We sought to identify an online cognitive screening tool for assessing mental capacity through the measurement of executive function. METHODS: A mixed elderly sample of 45 individuals, aged 65 years and older, were screened with the Montreal Cognitive Assessment (MoCA) and the modified Cambridge Brain Sciences Battery. RESULTS: Two computerized tests from the Cambridge Brain Sciences Battery were shown to provide information over and above that obtained with a standard cognitive screening tool, correctly sorting the majority of individuals with borderline MoCA scores. CONCLUSIONS: The brief computerized battery should be used in conjunction with standard tests such as the MoCA in order to differentiate cognitively intact from cognitively impaired older adults.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.073
GPT teacher head0.343
Teacher spread0.270 · 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