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Record W2467824825 · doi:10.1123/tsp.2016-0001

The Effects of Cognitive General Imagery Use on Decision Accuracy and Speed in Curling

2016· article· en· W2467824825 on OpenAlexaffabout
Nicole Westlund Stewart, Craig Hall

Bibliographic record

VenueThe Sport Psychologist · 2016
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsWestern University
Fundersnot available
KeywordsCurlingPsychologyMental imageClubKinesthetic learningIntervention (counseling)CognitionApplied psychologyDevelopmental psychologyMedicineEngineering

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the effects of a 6-week CG imagery intervention on strategic decision-making in curling. A secondary purpose was to determine whether curlers’ imagery ability and CG imagery use would be improved. Eleven varsity curlers from a Canadian postsecondary institution engaged in weekly guided imagery sessions that were held at the curling club before their regularly scheduled team practices. Curlers’ response times on a computerized curling strategy assessment significantly improved from baseline to post-intervention ( p < .05). In addition, their kinesthetic imagery ability, CG imagery use, and MG-M imagery use significantly increased ( p < .05). These results suggest that when curlers are exposed to new scenarios, they learn to store, process, and retrieve relevant information quicker (Simon & Chase, 1973). From a practical standpoint, CG imagery training can improve curlers’ strategy performance, including their ability to use various strategies in game situations.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.279
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.362
Teacher spread0.333 · 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

Citations17
Published2016
Admission routes2
Has abstractyes

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