The state of cognitive functions in relation to motor vehicle driving authorization for seniors. Subtitle: "New short cognitive tests" and Montreal Cognitive Assessment.
Bibliographic record
Abstract
INTRODUCTION: By the age of 65, every driver holding a valid driving license is required to undergo a compulsory medical examination according to Act 361/2000 Coll. The purpose of the examination should be to examine not only physical, but also psychosocial and cognitive factors that can affect the ability to drive safely. However, the extension of the validity of a driving license may have a considerable impact on the preservation of the existing self-sufficiency. GOALS: To determine the relationship of anamnestic data on the state of driving a motor vehicle with the state of cognitive functions. As a secondary goal, the work asks whether there is a correlation between the results of the Montreal cognitive test (MoCA-CZ1) with newly created memory screening tests (POBAV, ALBA and DOZNAT). METHODOLOGY: The research was based on a qualitative examination of the 39 drivers older than 65 years. Drivers were assessed by the state of cognitive function according to the Montreal Cognitive Test, and were then examined by "new short cognitive tests" targeting different types of memory. Finally, the participants filled out the questionnaire on subjective evaluation of driving skills. RESULTS: Dependence was found between the driving frequency and the groups of drivers with cognitive impairment and...
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.002 | 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".