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Record W4400561227 · doi:10.1152/jn.00090.2024

Biomechanical costs influence decisions made during ongoing actions

2024· article· en· W4400561227 on OpenAlexafffund
Cesar Augusto Canaveral, William Lata, Andrea M. Green, Paul Cisek

Bibliographic record

VenueJournal of Neurophysiology · 2024
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversité de Montréal
FundersFonds de recherche du Québec – Nature et technologiesFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaFonds de recherche du Québec
KeywordsPoint (geometry)Computer scienceMovement (music)Tracking (education)Path (computing)Cognitive psychologySimulationPsychologyMathematics

Abstract

fetched live from OpenAlex

In this study, we aim to shed light on how biomechanical factors influence decisions made during ongoing actions. Previous work suggested that decisions made during actions disregard biomechanical costs, in contrast to decisions made before movement. Our results challenge that proposal and suggest instead that the effect of biomechanical factors is dependent on the types of actions being compared (e.g., continuous tracking vs. point-to-point reaching). These findings contribute to our understanding of the dynamic interplay between biomechanical considerations and action choices during ongoing interactions with the environment.

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)0.002
metaresearch head score (Gemma)0.023
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.057
GPT teacher head0.357
Teacher spread0.300 · 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

Citations14
Published2024
Admission routes2
Has abstractyes

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