Emotions as Intermediaries for Implicit Memory Retrieval Processing: Evidence Using Word and Picture Stimuli
Bibliographic record
Abstract
The significance of emotions are seldom the focus of studies especially those concerning implicit memory. As a result, little is known about the effects of emotions on such memory. In two experiments, perceptual identification test was used to investigate the effects of emotional words and pictures on implicit memory. In Experiment 1, participants viewed lists of positive, negative and neutral words and in Experiment 2, participants saw lists of positive, negative and neutral pictures. Perceptual identification test was conducted after a 30 minute interval. Results showed that participants remembered better on implicit memory when information was with positive valence rather than negative valence: positive pictures and words were remembered more than negative pictures and words. However, the difference in types of information only emerged when the valence was positive. In this case, participants had an advantage for words over pictures only when these were presented with positive emotions, not with negative ones. The findings provide evidence for the significant mediating role of valence on implicit memory retrieval processes.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".