A DERIVED TRANSFER OF ELICITING EMOTIONAL FUNCTIONS USING DIFFERENCES AMONG ELECTROENCEPHALOGRAMS AS A DEPENDENT MEASURE
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Bibliographic record
Abstract
Emotional responses have specific electroencephalographic (EEG) signatures that arise within a few hundred milliseconds post-stimulus onset. In this experiment, EEG measures were employed to assess for transfer of emotional functions across three 3-member equivalence classes in an extension of Dougher, Auguston, Markham, Greenway, & Wulfert's (1994) seminal work on the transfer of arousal functions. Specifically, 12 human participants were trained in the following match-to-sample performances A1 = B1, A2 = B2, A3 = B3 and B1 = C1, B2 = C2, B3 = C3. After successfully testing for the emergence of symmetry relations (B1 = A1, B2 = A2, B3 = A3 and C1 = B1, C2 = B2, C3 = B3), visual images depicting emotionally positive and emotionally negative content were presented with A1 and A3, respectively, using a mixed stimulus pairing-compounding procedure. A2 was paired with emotionally neutral images. Next, EEG data were recorded as participants were exposed to a forced-choice recognition task with stimuli A1, B1, C1, A2, B2, C2, A3, B3, C3 and three novel stimuli A4, B4 and C4. Results yielded differential EEG effects for stimuli paired directly with emotional versus neutral images. Critically, differential EEG effects were also recorded across the C stimuli that were equivalently related to the A stimulus set. The EEG data coincide with previous reports of emotion-specific EEG effects, indicating that the initial emotional impact of a stimulus may emerge based on direct stimulus pairing and derived stimulus relations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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