The Bicycle Illusion: A new look at acuity, form, and motion interactions in conscious experience
Bibliographic record
Abstract
A bicycle rolling on a level surface alongside a fence of horizontally sagging chains appears to move up and down with the chains at certain viewing distances. In this bicycle illusion the relative vertical position of the bike follows the path of the chains. The illusion is different from motion capture because here a static form (fence) influences the perception of a moving form (bicycle), rather than the other way around. It is also distinguished from motion contrast because the moving bike follows the inducing chains rather than repelling from them. We took this sidewalk visual science into the lab by moving a disc horizontally on the screen and on top of two sinusoidal wavy lines. Our discoveries include: 1. The direction of the illusion is acuity dependent: at far viewing distances the disc appears to wiggle vertically in phase with the wavy lines (assimilation illusion) whereas at nearer viewing distances it appears to wiggle in counterphase to the lines (contrast illusion). 2. The assimilation illusion depends on the relative acuity of the static lines and the moving disc: the illusion is strengthened when the luminance contrast of the disc is reduced relative to the luminance contrast of the lines. 3. The contrast illusion is less dependent on the relative contrast of the disc and the lines. The bicycle illusion is therefore a novel preparation for studying the interactions between acuity, form and motion in conscious visual perception.
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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 | 0.000 | 0.001 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".