Breaking script: Deviations and postevent information in adult memory for a repeated event
Bibliographic record
Abstract
Summary Witnesses to industrial incidents may be asked to recall a single instance of a familiar event. This research systematically tested if deviations to what typically occurs and postevent information (PEI) enhanced reporting of an instance of a repeated event. Across 2 experiments, each participant experienced 5 food‐tasting instances; these instances comprised the repeated event. Half of the participants in both Experiments 1 (continuous deviation setting) and 2 (continuous deviation integrated) experienced a deviation to how the third instance occurred. Also, half of the participants in both experiments received PEI about the third instance. All participants demonstrated superior reporting for the first instance of the repeated event. The continuous deviation setting in Experiment 1 enhanced reporting for all 5 instances of the repeated event (general effect). In Experiment 2, participants who received a continuous deviation integrated and PEI demonstrated superior reporting for the first and third instances of the event (targeted effect).
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".