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Record W2566709408 · doi:10.3233/jad-160995

Investigating Simulated Driving Errors in Amnestic Single- and Multiple-Domain Mild Cognitive Impairment

2016· article· en· W2566709408 on OpenAlexafffund
Megan A. Hird, K Veselý, Corinne E. Fischer, Simon J. Graham, Gary Naglie, Tom A. Schweizer

Bibliographic record

VenueJournal of Alzheimer s Disease · 2016
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsBaycrest HospitalUniversity of TorontoUniversity Health NetworkToronto Rehabilitation InstituteSunnybrook Health Science CentreSunnybrook HospitalSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsCognitive impairmentAudiologyCognitionPsychologyMedicinePhysical medicine and rehabilitationNeuroscience

Abstract

fetched live from OpenAlex

The areas of driving impairment characteristic of mild cognitive impairment (MCI) remain unclear. This study compared the simulated driving performance of 24 individuals with MCI, including amnestic single-domain (sd-MCI, n = 11) and amnestic multiple-domain MCI (md-MCI, n = 13), and 20 age-matched controls. Individuals with MCI committed over twice as many driving errors (20.0 versus 9.9), demonstrated difficulty with lane maintenance, and committed more errors during left turns with traffic compared to healthy controls. Specifically, individuals with md-MCI demonstrated greater driving difficulty compared to healthy controls, relative to those with sd-MCI. Differentiating between different subtypes of MCI may be important when evaluating driving safety.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.067
GPT teacher head0.374
Teacher spread0.306 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations22
Published2016
Admission routes2
Has abstractyes

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