Orientation discrimination in noise: 7-year-olds are noisier than adults
Bibliographic record
Abstract
We used a new high contrast stimulus containing a variable amount of orientation signal in unoriented noise (Jones et al., 2003) to test orientation discrimination in visually normal 7-year-olds and adults (n = 16/grp). The task on each trial was to indicate whether the signal was oriented horizontally or vertically. Percent signal was varied according to a QUEST staircase procedure and thresholds were taken as the lowest orientation signal for which performance was 82% correct. Across 4 runs, stimulus size decreased systematically from 6 − 0.75 deg. In a 5th run, we retested the 6 deg stimulus to rule out fatigue effects. Thresholds were higher in children than in adults and varied with stimulus size (ANOVA, p < .0002 for both). Specifically, at both ages, thresholds improved as size increased from 0.75 – 3 deg (p < .005 for all) and then reached an asymptote, showing no further improvement beyond 3 deg (p > .70). At asymptote, children required 18% signal to discriminate orientation accurately whereas adults required only 12%, indicating that intrinsic noise may be 1.5 times higher in 7-year-olds than in adults. Because contrast sensitivity and motion coherence thresholds are mature by 7 years of age (Ellemberg et al., 1999, 2002), the ability to extract a stationary oriented signal from noise likely involves different neural mechanisms that mature more slowly.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".