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Record W4400983578 · doi:10.1037/xhp0001219

Action plan discarding leads to unbinding of action features.

2024· article· en· W4400983578 on OpenAlexaff
Viola Mocke, Christian Beste, Bernhard Pastötter, Wilfried Kunde

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsAction (physics)Computer scienceHuman multitaskingRepresentation (politics)Perspective (graphical)PsychologyArtificial intelligenceCognitive psychologyPolitical science

Abstract

fetched live from OpenAlex

Action planning can be construed as the temporary binding of action features to form a representation known as an action file. This file is distinct from other possible, but currently not required actions of the behavioral repertoire. To further this action file approach, we investigated what happens with an initially planned action, which however, is discarded before execution. In two experiments we found consistent evidence for a quick unbinding of action features with discarding. Other possible mechanisms that action discarding might invoke, be it the paradox strengthening of a discarded action plan, the selective suppression of the otherwise intact plan, or the global suppression of all subsequent action, were not or at least less consistently supported. These findings provide a novel perspective on inhibitory action control, which we discuss with respect to its applications to other instances of such inhibitory control as studied in multitasking, stop-signal, directed forgetting, or response-reprogramming paradigms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.670

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.275
GPT teacher head0.492
Teacher spread0.217 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

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