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Record W2025968586 · doi:10.1080/13854040590967072

Fine Tuning Recommendations for Older Adults with Memory Complaints: Using the Independent Living Scales with the Dementia Rating Scale

2006· article· en· W2025968586 on OpenAlexaff
Anne Baird

Bibliographic record

VenueThe Clinical Neuropsychologist · 2006
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsDementiaClinical Dementia RatingRating scalePsychologyNeuropsychologyDepression (economics)Clinical psychologyCognitionActivities of daily livingEffects of sleep deprivation on cognitive performanceGerontologyCognitive impairmentPsychiatryMedicineDevelopmental psychologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this study was to describe how functional test performance changed as global cognitive functioning dropped, as well as to examine the relationship of demographic variables and depression with functional test results. We found that level of performance on the Independent Living Scales (ILS) correlated highly with Dementia Rating Scale (DRS) scores in 83 older adults presenting for clinical neuropsychological assessment, while correlations with demographic factors and depression were nonsignificant or modest. Based on DRS scores, we divided our sample into four groups: normal cognitive status, borderline cognitive impairment, likely mild dementia, and likely moderate dementia. ILS profiles of the borderline impairment and mild dementia groups were similar and reflected particularly poor performance on subscales tapping financial management and everyday memory. Individuals with likely moderate dementia were markedly impaired on all subscales.

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)0.005
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.066
GPT teacher head0.398
Teacher spread0.333 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations40
Published2006
Admission routes1
Has abstractyes

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