Combining 3D-MOT with motor and perceptual decision-making tasks: conception of a life-sized virtual perceptual-cognitive training paradigm
Bibliographic record
Abstract
Abstract The present study introduces a virtual life-sized perceptual-cognitive paradigm combining three dimensional multiple object tracking (3D-MOT) with motor (Experiment 1) or perceptual (Experiment 2) decision-making tasks. The objectives were to assess the impact of training on task performance and to determine the best training conditions for improvement and learning. Seventy-one participants were randomly trained under one of four training conditions (isolated 3D-MOT task, 3D-MOT simultaneously combined with a decision-making task, consolidated 3D-MOT and decision-making task, isolated decision-making task). Task performance was evaluated using speed thresholds, decision accuracy (%) and reaction time (s). Findings showed that the dual-task paradigm allowed satisfactory degrees of performance on both tasks despite an important dual-task cost. Interestingly, the results seemed to favor consolidated over simultaneous training for dual-task performance when 3D-MOT was combined with a motor task. The amount of attentional shared resources in regards to the nature of the additional task was discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".