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Record W7034093872

Stav kognitivních funkcí ve vztahu k oprávnění řízení motorových vozidel u seniorů. Podtitul: "Nové krátké kognitivní testy" a Montrealský kognitivní test.

2018· dissertation· en· W7034093872 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2018
Typedissertation
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionPsychosocialAffect (linguistics)Montreal Cognitive AssessmentTest (biology)Work (physics)LicenseCognitive test
DOInot available

Abstract

fetched live from OpenAlex

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...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.242
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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