Bibliographic record
Abstract
Directional information can be extracted from scrambled point-light displays that are devoid of all structural cues prompting the suggestion of a distinct local mechanism in biological motion perception that may serve as a general “life detector” (Troje & Westhoff, 2006). We investigated this hypothesis by testing the perception of both animacy and direction from point-light stimuli. Coherent and scrambled point-light displays of humans, cats, and pigeons that were upright or inverted were embedded in a random dot mask and presented in saggital view to two groups of naïve observers (n = 12/grp). The first group assessed the animacy of the walker on a six-point Likert scale and the second group discriminated the direction of walking. Across blocks, stimulus duration varied from 200 – 1000 ms. Coherent stimuli appeared more animate than scrambled stimuli (p [[lt]] 0.001) and inversion decreased animacy ratings (p [[lt]] 0.001), although more substantially for coherent than for scrambled walkers (p = 0.007). Similarly, discrimination accuracies were higher for coherent versus scrambled stimuli (p [[lt]] 0.001) and inversion decreased performance (p [[lt]] 0.001), but more substantially for coherent than for scrambled walkers (p = 0.004). Both animacy ratings and discrimination accuracies did not differ for animal type (ps [[gt]] 0.200) nor stimulus duration (ps [[gt]] 0.300). The results indicate that like the ability to discriminate direction, the perception of animacy from scrambled displays is orientation-specific. We suggest that the responsible mechanism uses a dynamic, gravity-dependent framework to assess the presence of life in the environment and is remarkably robust, operating efficiently at limited exposure times.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.075 | 0.037 |
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".