The Kappa Effect With Only Two Visual Markers
Bibliographic record
Abstract
The kappa effect is a spatiotemporal illusion where duration is overestimated with the increase of space. This effect is typically demonstrated with three successive stimuli marking two neighboring empty time intervals, and the classical imputed velocity model, in principle, does not help to predict any spatial effects when only two stimuli, marking single intervals, are presented on each trial. We thus conducted three experiments, examining requirements for the occurrence of the kappa effect with only two visual stimuli. An interstimulus interval between the two stimuli was 217 (short) or 283 ms (long), and participants categorized the presented interval as ‘short’ or ‘long’. The key finding is that participants tended to respond ‘short’ more frequently than ‘long’ when both stimuli were delivered from the same location, whereas the relative frequency of ‘long’ responses was increased when the two stimuli were delivered from different locations in most directions (i.e., horizontally, vertically, diagonally; Experiment 1). This kappa effect clearly occurred when each stimulus was located 8° apart from the fovea in visual angle, but it was reduced when each stimulus was further deviated from the fovea, regardless of whether the two stimuli were presented in the vertical or the horizontal direction (Experiments 2 and 3). Moreover, increasing the spatial distance between the two stimuli from 15 to 30 cm magnified the effect only in a limited condition (Experiment 3). Implications of these results were discussed in terms of the Bayesian model predicting the effects of spatial acuity.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".