Bibliographic record
Abstract
To further explore how memory influences time judgments, we conducted two experiments on the lifespan of temporal representations in memory. Penney et al (2000, Journal of Experimental Psychology Human Perception and Performance 26 1770-1787) reported that the perceived duration of auditorily and visually marked intervals differs only when both marker-type intervals are compared directly. This finding can be explained by a 'memory-mixing' process, whereby the memory trace of previous intervals influences the perception of upcoming ones, which are then added to the memory content. In the experiments discussed here, we manipulated the mixing mode of auditory/visual signal presentations. In experiment 1, signals from the same modality were either grouped by blocks or randomised within blocks. The results showed that the auditory/visual difference decreased but remained present when modalities were grouped by blocks. In experiment 2, we used a line-segmentation task. The results showed that, after a training block was performed in one modality, the perceived duration of signals from the other modality was distorted for at least 30 trials and that the magnitude of the difference decreased as the block went on. The results of both experiments highlight the influence of memory on time judgments, providing empirical support to, and quantitative portrayal of, the memory-mixing process.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".