Executive function deficits in persons with mild cognitive impairment: A study with a Tower of London task
Bibliographic record
Abstract
This study assessed executive functions in persons with mild cognitive impairment (MCI) using the Tower of London (TOL). A second objective was to study the impact of three types of problem selected according to the presence or absence of a "trigger." A trigger (T) is an incitation to the participant, at the first move, to move a ball to its final position according to the model. A positive trigger (T+) is helpful, while a negative trigger (T-) creates an obstruction. Some problems have no trigger (N). This study includes 81 participants with MCI. After follow-up, one year later, two subgroups were distinguished: (a) 51 (63%) participants did not convert or decline (stable MCI); (b) 30 (37%) participants showed significant decline or progressed to dementia (decliner MCI). Persons with MCI were compared to an older adult group matched with respect to sex, age, and education. For the successes, there was a significant group difference between the three types of problem. The post hoc analysis showed that T+ took significantly less time than N or T-. There were significantly more successes for T+ than N, and these two types of problem had more success than T-. For "total number of moves," there was no significant difference between the groups. In post hoc analysis, T- involved more moves than N or T+. In qualitative analysis, T- MCI decliners produced significantly more rule breakings than the stable MCI and controls. A dysfunction in self-monitoring is a characteristic feature of persons with MCI.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".