Sleep and testing both strengthen and distort story recollection
Bibliographic record
Abstract
Over time, memories lose episodic detail and become distorted, a process with serious ramifications for topics such as 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, transformation, 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 retrieval practice or listen-only study condition, and either a sleep or wake delay group. A significant interaction for accuracy was observed between delay group and study condition, with higher accuracy after sleep compared to wake, but only in the absence of retrieval practice. However, sleep and retrieval practice also led to more inferences of non-presented, but story related information, via a second significant delay group by study condition interaction. These findings suggest that both sleep and retrieval practice contribute equally 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 | 0.000 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".