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Record W2067291110 · doi:10.1080/13554791003620306

Shifting efficacy, distribution of attention and controlled processing in two subtypes of mild cognitive impairment: Response time performance and intraindividual variability on a visual search task

2010· article· en· W2067291110 on OpenAlexaff
Paula McLaughlin, Michael Borrie, Susan Murtha

Bibliographic record

VenueNeurocase · 2010
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsWestern UniversityYork University
Fundersnot available
KeywordsVisual searchPsychologyCognitionAudiologyTask (project management)Cognitive psychologyDevelopmental psychologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

A visual search task was used to investigate how visual attention and intraindividual variability changes with mild cognitive impairment (MCI). Specifically, we examined the contribution of shifting efficacy, distribution of attention, and controlled processing to declines in visual attention in two groups with MCI (single-domain amnestic and multi-domain amnestic), and measured changes in intraindividual variability. Our results demonstrate that visual search performance is attenuated in multi-domain amnestic MCI, but not single-domain amnestic MCI. In addition, we found that the multi-domain amnestic MCI group was more variable than the older controls and single-domain amnestic MCI participants. These between-group differences in search efficacy and intraindividual variability increased as a function of task complexity. We attribute these decrements in performance to changes in the control of attention and shifting efficacy, but not the distribution of 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.012
GPT teacher head0.327
Teacher spread0.315 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2010
Admission routes1
Has abstractyes

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