Football referee's dilemma: negotiation between motor and cognitive tasks
Bibliographic record
Abstract
BACKGROUND: Football referees are exposed to a substantial level of motor and cognitive load during a game and perform dual tasks (DT) to make the best decisions. The present cross-sectional study aimed to investigate referees' motor performances during DT with different cognitive loads and compare their performances and those of the athletes. METHODS: Recruited 42 male referees and 60 male athletes completed the Edgren Side Step Test (ESST) as a single motor task (ST) and Multiple Object Tracking (MOT) Test at two different speeds (240 ms to 300 ms) at cognitive ST. Then, the tests were conducted concurrently as DT. Dual-task costs (DTC) were calculated. RESULTS: The comparison of ESST ST scores revealed that the scores of the referees were significantly higher than those of the athletes (P<0.001). The ESST and MOT scores of referees and the athletes significantly decreased during the DT (P<0.001 in both). Comparison of groups showed that the referees' ESST scores were significantly higher during the DT (P=0.026), while the groups' responses were similar regarding MOT scores (P=0.476). No differences were found in motor and cognitive performance DTC scores between the groups (P=0.465, P=0.184, respectively). CONCLUSIONS: DT reduced the motor and cognitive performances of both referees and athletes. Considering the importance of referees' motor and cognitive performance and ability to make correct decisions during the match, it is thought that training aimed at developing DT performances can be useful.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".