Investigating the application of “Guttmann Cognitest”® in older adults and people with acquired brain injury
Bibliographic record
Abstract
Introduction: , which includes seven computerized tasks designed to assess main cognitive functions, revealed in a previous validation study to be a potential useful tool to assess cognitive functioning in healthy middle-aged adults. Method: Here, we present results from a validation in two different populations: one consisting of older adults, and the other comprising young and middle-aged individuals, some of them affected by acquired brain injury. To perform a convergent validity test, older adults were also administered with the MOCA, while young and middle-aged individuals were administered with a short neuropsychological assessment including gold-standard neuropsychological tests. We also conducted sensitivity and specificity analysis to establish the utility of this instrument in identifying potential cognitive dysfunctions in the two groups. Results: Results demonstrated strong convergent validity as well as good specificity and sensitivity characteristics. Discussion: This tool is a valid and useful instrument to assess cognitive functioning and detecting potential cases of cognitive dysfunctions in older adults and clinical populations.
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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 | 0.006 |
| 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".