Bibliographic record
Abstract
Although early research implicated the amygdala in automatic processing of negative information, more recent research suggests that it plays a more general role in processing the motivational relevance of various stimuli, suggesting that the relation between valence and amygdala activation may depend on contextual goals. This study provides experimental evidence that the relation between valence and amygdala activity is dynamically modulated by evaluative goals. During functional magnetic resonance imaging, participants evaluated the positive, negative, or overall (positive plus negative) aspects of famous people. When participants were providing overall evaluations, both positive and negative names were associated with amygdala activation. When they were evaluating positivity, positive names were associated with amygdala activity, and when they were evaluating negativity, negative names were associated with amygdala activity. Evidence for a negativity bias was found; modulation was more pronounced for positive than for negative information. These data suggest that the amygdala flexibly processes motivationally relevant evaluative information in accordance with current processing goals, but processes negative information less flexibly than positive information.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".