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Record W2073860270 · doi:10.1080/00222890309602126

Acquisition and Automatization of a Complex Task: An Examination of Three-Ball Cascade Juggling

2003· article· en· W2073860270 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

VenueJournal of Motor Behavior · 2003
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsYork University
Fundersnot available
KeywordsAutomaticityTask (project management)PsychologyCascadeCognitive psychologyDreyfus model of skill acquisitionComputer scienceCognitionNeuroscienceEngineering

Abstract

fetched live from OpenAlex

The learning patterns of 3-ball cascade juggling from acquisition until automaticity were examined in 10 participants. On the basis of outcome measures derived from 26 practice sessions and 4 periodic probe sessions, the authors differentiated participants into 3 distinct learning types: a proficient group, an emerging group, and a single late learner. The proficient group was distinguished by how rapidly they learned and automatized performance. Most interesting, an inverse response cost (i.e., performance boost) on the secondary task was found in the majority of proficient group members during the dual-task condition. The present results are discussed in relation to the P. L. Ackerman model (1987, 1988) of complex skill acquisition as is the significance of the inverse response cost finding.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
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 head0.053
GPT teacher head0.287
Teacher spread0.233 · 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