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Record W7037404442

The effect of state anxiety on the online and offline control of fast target directed movements

2012· article· en· W7037404442 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAnxietyTask (project management)Movement (music)Control (management)AfferentTrajectoryReflection (computer programming)
DOInot available

Abstract

fetched live from OpenAlex

In target directed aiming, afferent information is used to adjust limb trajectories during movement execution (i.e., online) and to enhance the programming of subsequent trials (i.e., offline). The objective of the present study was to determine the influence of state anxiety on both online and offline afferent information processing for the first time. Participants practiced either a directional aiming task (Experiment 1) or an amplitude aiming task (Experiment 2) without anxiety before being transferred to a high anxiety condition. In both Experiments, within subject SD was calculated throughout the limb trajectory and was then compared between the low and high anxiety conditions. Results revealed that anxiety resulted in a decrement in performance. Furthermore, use of afferent information to adjust movement trajectories online was disrupted when movements were performed with anxiety, whereas there were no differences in the offline processing of afferent information between the low anxiety and high anxiety conditions. These findings indicated that state anxiety leads to a breakdown in the reflexive processes associated with the online control and not the less reflexive processes involved in movement programming and parameterisation.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.080

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 head0.007
GPT teacher head0.177
Teacher spread0.169 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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