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Record W2757814211 · doi:10.1093/geronb/gbx115

A Comprehensive Comparison of Quantifications of Intraindividual Variability in Response Times: A Measurement Burst Approach

2017· article· en· W2757814211 on OpenAlexafffund
Robert S. Stawski, Stuart MacDonald, Paul Brewster, Elizabeth Muñoz, Eric Cerino, Drew Halliday

Bibliographic record

VenueThe Journals of Gerontology Series B · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute on AgingNational Institutes of HealthMichael Smith Health Research BC
KeywordsContrast (vision)CognitionStatisticsAudiologyPsychologyMedicineComputer scienceMathematicsArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

OBJECTIVES: To formally identify and contrast the most commonly-employed quantifications of response time inconsistency (RTI) and elucidate their utility for understanding within-person (WP) and between-person (BP) variation in cognitive function with increasing age. METHOD: Using two measurement burst studies of cognitive aging, we systematically identified and computed five RTI quantifications from select disciplines to examine: (a) correlations among RTI quantifications; (b) the distribution of BP and WP variation in RTI; and (c) the comparability of RTI quantifications for predicting attention switching. RESULTS: Comparable patterns were observed across studies. There was significant variation in RTI BP as well as WP across sessions and bursts. Correlations among RTI quantifications were generally strong and positive both WP and BP, except for the coefficient of variation. Independent prediction models indicated that slower mean response time (RT) and greater RTI were associated with slower attention switching both WP and BP. For selecting simultaneous prediction models, collinearity resulted in inflated standard errors and unstable model estimates. DISCUSSION: RTI reflects a novel dimension of performance that is a robust and theoretically informative predictor of BP and WP variation in cognitive function. Among the plenitude of RTI quantifications, not all are interchangeable, nor of comparable predictive utility.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.561
GPT teacher head0.475
Teacher spread0.086 · 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.

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

Citations60
Published2017
Admission routes2
Has abstractyes

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