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Record W2098443872 · doi:10.1017/s0140525x01490108

Perception and action planning: Getting it together

2001· article· en· W2098443872 on OpenAlexaff
David A. Westwood, Melvyn A. Goodale

Bibliographic record

VenueBehavioral and Brain Sciences · 2001
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsWestern University
Fundersnot available
KeywordsPerceptionAction (physics)Unconscious mindControl (management)Cognitive scienceCognitive psychologyComputer scienceVisual perceptionPsychologyPoint (geometry)Artificial intelligenceNeuroscienceMathematics

Abstract

fetched live from OpenAlex

Hommel et al. propose that high-level perception and action planning share a common representational domain, which facilitates the control of intentional actions. On the surface, this point of view appears quite different from an alternative account that suggests that “action” and “perception” are functionally and neurologically dissociable processes. But it is difficult to reconcile these apparently different perspectives, because Hommel et al. do not clearly specify what they mean by “perception” and “action planning.” With respect to the visual control of action, a distinction must be made between conscious visual perception and unconscious visuomotor processing. Hommel et al. must also distinguish between the what and how aspects of action planning, that is, planning what to do versus planning how to do it.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.308

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 communication0.0000.000
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 head0.180
GPT teacher head0.380
Teacher spread0.201 · 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 designObservational
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

Citations3
Published2001
Admission routes1
Has abstractyes

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