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Record W1974431071 · doi:10.1007/s00426-006-0101-3

Action–effect anticipation in infant action control

2006· article· en· W1974431071 on OpenAlexaff
Petra Hauf, Gisa Aschersleben

Bibliographic record

VenuePsychological Research · 2006
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsAnticipation (artificial intelligence)Action (physics)PsychologyDevelopmental psychologyCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

There is increasing evidence that action effects play a crucial role in action understanding and action control not only in adults but also in infants. Most of the research in infants focused on the learning of action-effect contingencies or how action effects help infants to infer goals in other persons' actions. In contrast, the present research aimed at demonstrating that infants control their own actions by action-effect anticipation once they know about specific action-effect relations. About 7 and 9-month olds observed an experimenter demonstrating two actions that differed regarding the action-effect assignment. Either a red-button press or a blue-button press or no button press elicited interesting acoustical and visual effects. The 9-month olds produced the effect action at first, with shorter latency and longer duration sustaining a direct impact of action-effect anticipation on action control. In 7-month olds the differences due to action-effect manipulation were less profound indicating developmental changes at this age.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.224
GPT teacher head0.543
Teacher spread0.319 · 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 source (direct Gemma or distilled Codex), 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

Citations36
Published2006
Admission routes1
Has abstractyes

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