Numerical Context and Time Perception: Contrast Effects and the Perceived Duration of Numbers
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Bibliographic record
Abstract
In the current study, we examined how the contextual repetition of magnitude information presented in either symbolic (Arabic digits) or nonsymbolic (numerosities) formats impacted on the perceived duration of a later occurring target number. The results of the current study demonstrated a time-magnitude bias in which, on average, large magnitude target numbers were judged to last for longer durations relative to small magnitude target numbers, regardless of notation (symbolic number and numerosity). Furthermore, context effects were found, in which a greater discrepancy in the target's magnitude from the initial context led to longer perceived duration ratings. However, this was found to be asymmetrical, occurring only for large magnitude targets. Additionally, the type of context effect was shown to be determined by whether the context was presented in the same notation as the target or a different notation.
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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 it