Sleep and retrieval practice both strengthen and distort story recollection
Bibliographic record
Abstract
Over time, memories lose episodic detail and become distorted, a process with serious ramifications for eyewitness identification. What are the processes contributing to such transformations over time? We investigated the roles of post-learning sleep and retrieval practice in memory accuracy and distortion, using a naturalistic story recollection task. Undergraduate students listened to a recording of the "War of the Ghosts," a Native American folktale, and were assigned to either a sleep or wake delay group, and either a retrieval practice or listen-only study condition. We found higher accuracy after sleep compared to wake in the listen-only condition, but not in the retrieval practice condition. This effect was driven by participants in the wake, retrieval practice condition showing superior memory compared to the wake, listen-only condition. A similar pattern was found for memory distortion, with both sleep and retrieval practice being associated with more inferences of nonpresented, but story-related information, compared to the wake, listen-only condition. These findings suggest both sleep and retrieval practice contribute to narrative memory stabilization and distortion.
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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 | 0.005 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".