MétaCan
Menu
Back to cohort
Record W4385654683 · doi:10.1080/23279095.2023.2243358

Repeated stroboscopic vision training improves anticipation skill without changing perceptual-cognitive skills in soccer players

2023· article· en· W4385654683 on OpenAlexaff
Leonardo de Sousa Fortes, Heloiana Faro, Jocelyn Faubert, Carlos Gilberto de Freitas-Junior, Dalton de Lima‐Júnior, Sebastião Sousa Almeida

Bibliographic record

VenueApplied Neuropsychology Adult · 2023
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAnticipation (artificial intelligence)StroboscopeAthletesPsychologyPerceptionCognitionTracking (education)Cognitive psychologyPhysical therapyComputer scienceArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

In this study we aimed to analyze the repeated effect of stroboscopic vision training on perceptual-cognitive skills in soccer players. A total of 28 male soccer players participated in this experimental and randomized study with parallel groups. The soccer players were pair-matched according to perceptual-cognitive skills and randomized into two groups: Stroboscopic vision training and Control. Multiple object tracking, anticipation, and decision-making skills were measured before and after the 8-week intervention. An increase in multiple object tracking (p < 0.05) and decision-making skills (p < 0.05) from baseline to post-experiment was found in both groups without main group effect (p > 0.05). The findings showed an increase in anticipation skill from baseline to post-experiment in both groups (p < 0.05), with higher anticipation skill for the stroboscopic group than in the control group post-experiment (p < 0.05). Thus, we conclude that repeated stroboscopic vision training could improve anticipation skill in soccer athletes.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.027
GPT teacher head0.359
Teacher spread0.332 · 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

Citations17
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueApplied Neuropsychology AdultSame topicSport Psychology and PerformanceFrench-language works237,207