Determining eyewitness identification accuracy using event‐related brain potentials (ERPs)
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Bibliographic record
Abstract
This study investigated the use of event-related brain potentials (ERPs) as a neurophysiological measure of eyewitness identification accuracy during a lineup task (ERP-lineup). Time delay between viewing the crime and completing the ERP-lineup (no-delay, 1-h delay and 1-week delay conditions) and culprit presence or absence were also manipulated. Results demonstrated that a P300 provided a reliable index of recognition of the culprit relative to the other lineup members across all time delay conditions. Although participants' accuracy decreased at the 1-week time delay compared to no delay and the 1-h time delay, the P300 effect remained strong for participants that made correct identifications irrespective of the time delay. In addition, the P300 was attenuated or was not elicited when the culprit was absent from the lineup.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it