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Record W2107692221

AGING AND WORKLOAD CAPACITY: DO OLDER ADULTS INTEGRATE VISUAL STIMULI DIFFERENTLY THAN YOUNGER ADULTS?

2008· article· en· W2107692221 on OpenAlex
Boaz M. Ben‐David, Ami Eidels, Wu Yan, Lulu Li

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of Fechner Day · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTownsendWorkloadCognitionPsychologyCognitive psychologyDevelopmental psychologyAudiologyPhysical medicine and rehabilitationComputer scienceMedicineNeuroscience
DOInot available

Abstract

fetched live from OpenAlex

The effect of aging on response times and on the processing capacity of redundant-visual signals is a neglected theme in the study of aging. In the redundant target design (RTD), an observer detects the presence of a target. A trial can include two (redundant), single, or no-targets. Do older-adults integrate visual stimuli differently than younger-adults? A new approach to capacity (Townsend & Nozawa, 1995) compares the processing of single- and redundant-target trials to compute an index of workload capacity. We discuss the implication of various theories of aging on Townsend’s capacity coefficient: Generalized cognitive slowing models with a single age-related slowing equation for all trials; Information degradation models linking sensory loss with cognitive tasks; and Models assuming a decrease in the efficiency of inhibiting distractors. Experimentally, we compare target- detection latencies and Townsend’s capacity for younger- and older-adults in RTD, examining the effects of distractor presence and absence for both groups.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.980

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.070
GPT teacher head0.314
Teacher spread0.245 · 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