A test battery for assessing biological motion perception
Bibliographic record
Abstract
Tests designed to measure biological motion perception have often confounded two or more distinct perceptual abilities. These abilities include structure-from-nonrigid-motion, figure-ground segregation, and processing of local motion invariants. We have developed a battery of tests that measure these abilities independently, in addition to higher level biological motion abilities including action recognition, movement style perception, and person recognition. Seventy-five participants completed the battery, allowing for an individual-differences analysis. The lack of correlation between scores on the tests provides support for the independence of the underlying processes. In order to assess robustness of the tests to differences in the experimental environment, and to measure test-retest reliability, we had 30 additional participants complete the battery both in the lab and on their home computers. There was no effect of environment for the majority of the tests. Together, the results suggest that the test battery efficiently measures the components of biological motion perception, and performs nearly as well under uncontrolled viewing conditions. One future use of the battery is to fully characterize the perceptual deficits of special populations with respect to 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".