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Record W4230497682 · doi:10.1093/geront/gnv576.03

EXPLORING STRATEGIES TO OPERATIONALIZE COGNITIVE RESERVE

2015· article· en· W4230497682 on OpenAlexaff

Bibliographic record

VenueThe Gerontologist · 2015
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsOperationalizationCognitive reserveCognitionPsychologyComputer scienceCognitive impairmentNeuroscienceEpistemology

Abstract

fetched live from OpenAlex

Using a coordinated analysis approach, we employed multilevel models to investigate the effect of education on the rate of decline measured with MMSE in preclinical stages of dementia in four longitudinal studies: Newcastle 85+ (3 waves), UK; Leiden 85+ (6 waves), Netherlands; 3 Cities (5 waves), France and OCTO-Twins (5 waves), Sweden.Higher education (>10 years) was associated with higher MMSE scores at the time of dementia diagnosis, compared to those with lower education in two of these studies (Newcastle 85+ & 3 Cities). Higher education had a moderating role on the rate of decline in the Newcastle 85+ (= 1.25, SE=0.26, p <0.01) but a reverse effect in the Leiden study (= -1.00, SE=0.43, p <0.05), where those with higher education had a stepper decline. This coordinated approach revealed no consistent protection for those with higher education, therefore this study did not fully support the cognitive reserve hypothesis.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.678
GPT teacher head0.457
Teacher spread0.220 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations0
Published2015
Admission routes1
Has abstractyes

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