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Record W2126813245 · doi:10.2466/pr0.102.2.532-538

Cognitive Demands of Error Processing

2008· article· en· W2126813245 on OpenAlex

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

VenuePsychological Reports · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAnticipation (artificial intelligence)PsychologyTask (project management)CognitionCognitive psychologyStimulus (psychology)AudiologyComputer scienceArtificial intelligenceNeuroscienceMedicine

Abstract

fetched live from OpenAlex

This study used a dual-task methodology to assess attention demands associated with error processing during an anticipation-timing task. A difference was predicted in attention demands during feedback on trials with correct responses and errors. This was addressed by requiring participants to respond to a probe reaction-time stimulus after augmented feedback presentation. 16 participants (8 men, 8 women) completed two phases, the reaction time task only and the anticipation-timing task with the probe RT task. False feedback indicating error and a financial reward manipulation were used to increase relevance of errors. Data supported the hypothesis that error processing is associated with higher cognitive demands than processing feedback denoting a correct response. Individuals responded with quicker probe reaction times during presentation of feedback on correct trials than on error trials. These results are discussed with respect to the cognitive processes which might occur during error processing and their role in motor learning.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.438
GPT teacher head0.480
Teacher spread0.042 · 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