Effect of motion discontinuities on discrimination of periodic trajectories
Bibliographic record
Abstract
Many biologically important motions are described by periodic trajectories. Radial frequency (RF) trajectories are one example, in which the motion of a difference of Gaussians (DOG) target moves along a path described by a sinusoidal deviation of the radius from a perfect circle (Or, Thabet, Wilkinson, & Wilson, 2011). Here we explore the hypothesis that visual processing of RF trajectories involves global spatio-temporal processes that are disrupted by motion discontinuity. To test this hypothesis, RF trajectories were used that interspersed smooth, continuous motion with three or four discontinuous jumps to other portions of the trajectory. These jumps were arranged so that the entire trajectory was traversed in the same amount of time as in the continuous motion control condition. The motion discontinuities increased thresholds by a factor of approximately 2.1 relative to continuous motion. This result provides support for global spatio-temporal processing of RF motion trajectories. Comparison with previous results suggests that motion discontinuities erase memory for earlier parts of the trajectory, thereby causing thresholds to be based on only the final segment viewed. Finally, it is shown that RF trajectories obey the 1/3 power law characteristic of biological motion.
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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 | 0.004 |
| 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 | 0.001 |
| 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".