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Record W3000001826 · doi:10.1123/mc.2019-0049

Performance-Stabilizing Synergies in a Complex Motor Skill: Analysis Based on the Uncontrolled Manifold Hypothesis

2020· article· en· W3000001826 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMotor Control · 2020
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsMcGill University
Fundersnot available
KeywordsThrowingHierarchyMathematicsBall (mathematics)Motor controlMotor learningStability (learning theory)PsychologyPhysical medicine and rehabilitationComputer scienceMathematical analysisMedicineMachine learningNeuroscienceEngineering

Abstract

fetched live from OpenAlex

The authors studied indices of stability (ΔV) of two time-varying variables, hand coordinate and velocity, during accurate throw of a small ball into the basket. Ten participants performed the throwing task with eyes-open (vision) and -closed (no vision) conditions. In the latter condition, participants closed their eyes prior to initiating the throw. The intertrial variance in the joint configuration space (and joint velocity space) was analyzed based on the uncontrolled manifold hypothesis. The results confirmed the presence of both coordinate- and velocity-stabilizing synergies (ΔV > 0). Intertrial variance was larger in the no-vision condition compared with the vision condition. Over the movement duration, ΔV did not change for the coordinate-related analysis but dropped consistently for the velocity-related analysis. The authors interpret the findings within the idea of hierarchical control and trade-off between synergy indices at different levels of the hierarchy.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.050
GPT teacher head0.225
Teacher spread0.175 · 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