Investigation of the psychological length of a 1-s interval with a time production task.
Bibliographic record
Abstract
Several studies using the production of 1-s intervals report instability in the results. This suggests that there is no clear representation of the value of 1 s in long-term memory. This instability may partly be explained by the specific methodological requirements of studies using 1-s production tasks. Typically, this task requires participants to produce 1-s intervals by either using two intermittent finger taps (one at the beginning and one at the end of the interval), or by continuously pressing a key for the duration of the second. The purpose of this study was to investigate the impact of two main factors on the production of 1-s intervals, namely the effects of kinesthetic cues (continuous press vs. two intermittent presses) and auditory cues (sound vs. no sound) during the production of each interval. Participants produced 30 1-s intervals under four conditions. The results showed significant effects of both kinesthetic and auditory factors on the produced intervals. The kinesthetic effects applied to both the accuracy (staying close to the 1-s target) and precision (minimizing intertrial variability), and the auditory effects were limited to accuracy. This study highlights that the expression of what is likely a representation of the psychological second in long-term memory is prone to much distortion. Explanations of this instability of the psychological second are explored, including the simultaneous involvement of circuits related to sub- (< 1 s) and supra-second (> 1 s) intervals and individual differences in the internal clock. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.010 |
| 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 | 0.001 | 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".