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Record W2130144589 · doi:10.1080/13803395.2011.589372

Glucose regulation is associated with attentional control performances in nondiabetic older adults

2011· article· en· W2130144589 on OpenAlexafffund
Christine Gagnon, Carol E. Greenwood, Louis Bherer

Bibliographic record

VenueJournal of Clinical and Experimental Neuropsychology · 2011
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsBaycrest HospitalUniversity of TorontoInstitut Universitaire de Gériatrie de MontréalUniversité du Québec à Montréal
FundersCanadian Institutes of Health Research
KeywordsStroop effectNeuropsychologyPsychologyCognitionDevelopmental psychologyTrail Making TestExecutive functionsTest (biology)AudiologyEffects of sleep deprivation on cognitive performanceAttentional controlCognitive psychologyClinical psychologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Less efficient glucose regulation, the ability to metabolize glucose, has been associated with poorer cognitive performances in older individuals not meeting criteria for type 2 diabetes ( Messier, Tsiakas, Gagnon, & Desrochers, 2010 ). Yet, the influence of glucose regulation on attentional functions, which are sensitive to aging, is still unclear. The present study examined the relationship between glucose regulation and performances on attentional tasks in nondiabetic older adults. Twenty-two participants (60 years and older) were tested on neuropsychological tests of attention (Trail Making test, modified Stroop test) and on a computerized dual task, after receiving a 50-g glucose drink. Participants with the worse glucose regulation committed more errors on the switching condition of the modified Stroop test (p < .05) and tended to make more errors in divided-attention trials of the computerized dual task (p = .05). Altogether, these results suggest that glucose regulation may transiently influence performances of metabolically healthy older adults on tasks requiring switching attention.

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)0.000
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 score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.039
GPT teacher head0.378
Teacher spread0.340 · 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

Citations10
Published2011
Admission routes2
Has abstractyes

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