Investigation of an EEG-based Indicator of Skill Acquisition as Novice Participants Practice a Lifeboat Maneuvering Task in a Simulator
Why this work is in the frame
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Bibliographic record
Abstract
In training, task proficiency is typically assessed through relevant performance measures. Such measures provide information about how effectively the individual can perform the task, but they give no insight about cognitive efficiency. Neural signals may provide this information regarding a trainee’s task proficiency that performance measures alone cannot. The purpose of this study was to investigate patterns in neural activity that are indicative of task proficiency. Ten novice participants completed ten trials of a maneuvering task in a lifeboat simulator while their neural activity was recorded via electroencephalography (EEG). Power spectral features were used along with linear discriminant analysis to classify the data from pairs of adjacent trials. Repeated measures mixed model linear regression showed that, on average, the accuracy with which adjacent trials could be discriminated from each other decreased significantly over the course of training. The result indicates that with practice, the associated neural activity becomes more similar from trial to trial.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it