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Record W6920710796 · doi:10.6084/m9.figshare.11419251

The Canadian longitudinal study on aging as a platform for exploring cognition in an aging population

2019· article· en· W6920710796 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2019
Typearticle
Languageen
FieldPsychology
TopicCognitive Functions and Memory
Canadian institutionsnot available
Fundersnot available
KeywordsStroop effectCognitionLongitudinal studyCognitive testCognitive agingTest (biology)CohortPopulation

Abstract

fetched live from OpenAlex

Objective: We present descriptive information on the cognitive measures used in the Canadian Longitudinal Study on Aging (CLSA) Comprehensive Cohort, relate this to information on these measures in the extant literature, and identify key considerations for their use in research and clinical practice. Method: The CLSA Comprehensive Cohort is composed of 30,097 participants aged 45–85 years at baseline who provided a broad range of sociodemographic, physical, social, and psychological health information via questionnaire and took part in detailed physical and cognitive assessments. Cognitive measures included: the Rey Auditory Verbal Learning Test – immediate and 5-min delayed recall, Animal Fluency, Mental Alternation Test (MAT), Controlled Oral Word Association Test (COWAT), Stroop Test – Victoria Version, Miami Prospective Memory Test (MPMT), and a Choice Reaction Time (CRT) task. Results: CLSA Comprehensive Cohort sample sizes were far larger than previous studies, and performances on the cognitive measures were similar to comparable groups. Within the CLSA Comprehensive Cohort, main effects of age were observed for all cognitive measures, and main effects of language were observed for all measures except the CRT. Interaction effects (language × age) were observed for the MAT, MPMT Event-based score, all time scores on the Stroop Test, and most COWAT scores. Main effects of education were observed for all measures except for the MPMT Time score in the French sample, and interaction effects (age × education) were observed for the RAVLT (immediate and delayed) for the English sample and the Stroop Dot time for the French sample. Conclusion: This examination of the cognitive measures used in the CLSA Comprehensive Cohort lends support to their use in large studies of health and aging. We propose further exploration of the cognitive measures within the CLSA to make this information relevant to and available for clinical practice.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.017
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.007
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.321
GPT teacher head0.400
Teacher spread0.078 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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