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Record W3139073979 · doi:10.1080/23279095.2021.1896518

Determining affected memory domains in patients with amnestic mild cognitive impairment using computerized and interactive tests

2021· article· en· W3139073979 on OpenAlexafffund
Daniel Kroft, Mohamed Abo Aoun, Benjamin P. Meek, R. Bruce Bolster, Mandana Modirrousta

Bibliographic record

VenueApplied Neuropsychology Adult · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsSt. Boniface HospitalUniversity of Winnipeg
FundersFondation de l’Hôpital Saint-Boniface
KeywordsTask (project management)Cognitive psychologyEpisodic memoryCognitionMemory impairmentPsychologyCognitive impairmentObject (grammar)Spatial memoryAudiologyWorking memoryComputer scienceNeuroscienceMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

This study explores different episodic memory domains, namely object, temporal and spatial memory, affected in patients with a clinical diagnosis of single domain amnestic mild cognitive impairment (aMCI). 15 aMCI patients and 25 healthy controls were recruited and tested. Object, spatial, and temporal memory were tested using computerized tasks and again in interactive, real-world tasks. Controls outperformed patients on the object computerized task and showed a trend toward significance for the computerized spatial and temporal tasks, but there was no difference in spatial and temporal memory when using the interactive tasks, indicating the employment of compensatory mechanisms in patients to overcome some of the memory impairments associated with aMCI. These findings highlight that aMCI patients might delay seeking help due to compensatory mechanisms which mask their deficits in real-world situations.

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)0.000
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 score0.021
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.302
Teacher spread0.290 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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