Generalized Common Fate: Grouping by Common Luminance Changes
Bibliographic record
Abstract
A critical step toward object recognition is the segmentation of a scene into relevant regions. One of the most important cues for segmentation is that of common fate: Elements that move together are grouped together Here we describe a new instantiation of common fate, in which elements move together not through physical space, but through luminance space. Experiment I shows that when elements of a scene become brighter together or darker together, observers group those elements together Experiments 2 and 3 show that this effect is not due to the availability of fixed luminance differences between target and background regions, but requires common changes within each region in the direction of luminance over time. The effect is differentiated from the recently discovered grouping cue of temporal synchrony, and is considered instead to be an extension of Wertheimer's original grouping factor of common fate. Common fate for luminance, or generalized common fate, is an extremely strong cue for the segmentation of a scene, yielding a tremendous advantage over grouping by fixed luminance cues.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".