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Record W2130506872 · doi:10.1177/0956797611408733

One to Four, and Nothing More

2011· article· en· W2130506872 on OpenAlexaff
Jason P. Gallivan, Craig S. Chapman, Daniel K. Wood, Jennifer L. Milne, Daniel Ansari, Jody C. Culham, Melvyn A. Goodale

Bibliographic record

VenuePsychological Science · 2011
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsWestern University
FundersAssociation for Psychological Science
KeywordsPsychologyPerceptionLimit (mathematics)Cognitive psychologyCognitionTask (project management)Action (physics)Object (grammar)Visual perceptionNothingDomain specificityDepth perceptionCommunicationArtificial intelligenceComputer scienceNeuroscienceMathematics

Abstract

fetched live from OpenAlex

Much of the current understanding about the capacity limits on the number of objects that can be simultaneously processed comes from studies of visual short-term memory, attention, and numerical cognition. Consistent reports suggest that, despite large variability in the perceptual tasks administered (e.g., object tracking, counting), a limit of three to four visual items can be independently processed in parallel. In the research reported here, we asked whether this limit also extends to the domain of action planning. Using a unique rapid visuomotor task and a novel analysis of reach trajectories, we demonstrated an upper limit to the number of targets that can be simultaneously encoded for action, a capacity limit that also turns out to be no more than three to four. Our findings suggest that conscious perceptual processing and nonconscious movement planning are constrained by a common underlying mechanism limited by the number of items that can be simultaneously represented.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.205
GPT teacher head0.395
Teacher spread0.190 · 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 designTheoretical or conceptual
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

Citations62
Published2011
Admission routes1
Has abstractyes

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