Electrophysiological markers of voice familiarity
Why this work is in the frame
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Bibliographic record
Abstract
Our ability to discriminate and recognize human voices is amongst the most important functions of the human auditory system. The current study sought to determine whether electrophysiological markers could be used as objective measures of voice familiarity, by looking at the electrophysiological responses [mismatch negativity (MMN) and P3a] when the infrequent stimulus presented is a familiar voice as opposed to an unfamiliar voice. Results indicate that the MMN elicited by a familiar voice is greater than that elicited by an unfamiliar voice at FCz. The familiar voice also produced a greater P3a wave than that triggered by the unfamiliar voice at Fz. As both the MMN and the P3a were elicited as participants were instructed not to pay attention to incoming stimulation, these findings suggest that voice recognition is a particularly potent preattentive process whose neural representations can be objectively described through electrophysiological assessments.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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