The Development of Sensitivity to Biological Motion in Noise
Bibliographic record
Abstract
We investigated developmental changes in sensitivity to biological motion by asking 6-year-olds, 9-year-olds, and adults (twenty-four in each group) to discriminate point-light biological motion displays depicting one of a variety of human movements from scrambled versions of the same displays. When tested without noise dots, participants at all ages performed near ceiling levels and no differences in accuracy were found among the three age groups. Age differences emerged in the second task, in which we used a staircase procedure to determine threshold values of the number of noise dots that could be tolerated in producing a percentage correct value corresponding to a d' value of 1.4. Sensitivity to biological motion improved linearly with age (p < 0.01), with 6-year-olds performing significantly more poorly than adults. This immature performance contrasts with adult-like accuracy by 4 years of age for sensitivity to global motion (Parrish et al, 2005 Vision Research 45 827-837). The comparison implies an immaturity at 6 years of age in the neural networks involved specifically in the processing of biological motion, networks that may include the superior temporal sulcus (STS).
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".