Structure of four executive functioning tests in healthy older adults.
Bibliographic record
Abstract
The authors examined the factor structure of 4 indicators of executive functioning derived from 2 new (i.e., Hayling and Brixton) and 2 traditional (i.e., Stroop and Color Trails) tests. Data were from a cross-sectional sample of 55- to 85-year-old healthy adults (N=427) from the Victoria Longitudinal Study. Confirmatory factor analysis (LISREL 8.52) tested both a 2-factor model of Inhibition (Hayling, Stroop) and Shifting (Brixton, Color Trails) and a single-factor model. The 2-factor model did not fit the data because the covariance matrix of the factors was not positive definite. The single-factor model fit the data well, chi(2)(2, N=427)=0.32, p=.85, root-mean-square error of approximation (RMSEA)=.00, comparative fit index (CFI)=1.00, goodness-of-fit index (GFI)=1.00. Moreover, the single-factor structure of executive functioning was invariant (configural and metric) across gender, and invariant (configural with limited metric) across age. Structural relations showed that poorer executive functioning performance was related to older age and lower fluid intelligence, chi(2)(11, N=418)=23.04, p=.02, RMSEA=.05, CFI=.97, GFI=.98.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".