Influence of age and education on the processing of clustering and switching in verbal fluency tasks
Bibliographic record
Abstract
Verbal fluency (VF) is a widely used tool in neuropsychological assessment. OBJECTIVE: We aimed to investigate the influence of age and educational level on clustering and switching in three VF modalities: phonemic (PVF), semantic (SVF) and unconstrained (UVF). We evaluated type of cluster, mean cluster size, and quantity of clusters, intersections, and returns. A total of 260 healthy subjects were assessed. METHODS: Participants were divided into three age groups: young adults (18 to 39 years), middle-aged adults (40 to 59 years) and older adults (60 to 80 years) and into two groups of educational level: 1-8 years (low), 9 years or more (high). A two-way ANOVA analysis was conducted to analyze the effect of age and educational level and its interactions. A repeated measures ANOVA was performed to verify the performance during the task. RESULTS: A main effect of age was detected on the UVF and SVF scores for total switches, taxonomic clusters, and for the total semantic clusters on the SVF. There was a greater effect of educational level on total switches (UVF, PFV and SVF), taxonomic clusters (UVF and SVF), thematic clusters and total semantic cluster (UVF), phonemic and mixed clusters (PVF), mean cluster size (UVF and SVF) and intersections (SVF). Educational level had a greater effect on all three VF tasks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".