Three-dimensional multiple object tracking improves young adult cognitive abilities associated with driving: evidence for transfer to the useful field of view
Bibliographic record
Abstract
OBJECTIVES: 3-dimensional multiple object tracking (3D-MOT) and the useful field of view (UFOV) both claim to measure and train cognitive abilities, such as selective and divided attention implicated in driving safety. 3D-MOT is claimed to improve even young adult cognitive ability. If true, one would expect to observe the transfer of 3D-MOT training to UFOV performance mediated by way of shared underlying cognitive mechanisms. METHODS: We test this notion by assessing whether ten 30-min sessions of 3D-MOT training spread across 5 weeks improves UFOV performance relative to an active control group trained on a visual task and a challenging puzzle game (participants aged between 23 and 33 years old). RESULTS: The 3D-MOT training group exhibited significantly improved UFOV performance whereas the active control group exhibited only a small, statistically nonsignificant improvement in the task. CONCLUSIONS: This suggests that 3D-MOT and UFOV performance are likely dependent on overlapping cognitive abilities and helps support the assertion that these abilities can be trained and measured even in young adults. Such training could have implications for improving driver safety in both young and older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".