Bibliographic record
Abstract
Common fate is a fundamental law of Gestalt psychology: elements that move together are perceived as being part of the same object (Wertheimer, 1923). Although common fate suggests that the perception of motion drives object perception, the spatial arrangement of the elements also can have an effect on the perception of motion, even when that arrangement is perceived only via motion. For example, Uttal et al. (2000) showed that dots that moved in a common direction within a cloud of randomly moving dots were detected better when the target dots were arranged collinearily than when they were non-collinear. These results indicate that both motion direction and spatial organization are crucial for target detection in random dot motion displays. As we age, some aspects of our motion perception remain relatively unchanged, while other aspects are impaired. For example, the ability to integrate form and motion information in the context of higher-level visual stimuli, such as biological motion stimuli, seems to be impaired (Pilz et al., in press). Here, we investigated the effect of aging on the perception of common fate, and the way common fate interacts with form perception. In the current experiment, older (∼65 years) and younger (∼ 23 years) subjects detected a group (collinear or non-collinear) of four coherently moving dots that appeared in one of two sequentially presented sets of randomly moving dots with limited lifetime. The target dots always moved in a common direction, which varied across trials. Compared to younger subjects, older subjects showed a general decline in target detection based on common fate. This decline was significantly greater for non-collinear targets. These results indicate that with aging, form regularity is especially important for detecting coherently moving targets, which may underlie previous results regarding perception in higher-level visual tasks such as 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".