The letter in the crowd: Developmental trajectory of single letter acuity and foveal crowding
Bibliographic record
Abstract
Crowding (Stuart & Burian, 1962) refers to impaired target recognition caused by surrounding contours. Studies on developmental changes in crowding (Atkinson et al., 1988; Bondarko and Semenov, 2005; Semenov et al., 2000) fail to provide a clear picture. To investigate the developmental trajectory of foveal crowding, groups (N = 20/age group) of adults (mean age = 19.4 yrs, range 18 – 23 yrs) and children aged 5.5, 8.5 and 11.5 years (+/− 3 months) were asked to discriminate the orientation of a Sloan letter E. We first measured the single-letter threshold, defined as the stroke width discriminable at 79% correct performance. We then multiplied the single-letter threshold by 1.2 and surrounded it with flankers consisting of four sets of three bars randomly oriented horizontally or vertically. The crowding threshold was measured as the distance between the nearest edges of the flankers and the central letter yielding 79% correct performance. Mean single-letter thresholds were 1.0, 0.8, 0.8 and 0.8 arcmin for 5-, 8-, 11-year-olds and adults, respectively. Single-letter thresholds for 5-year-olds were significantly worse than those for all older age groups, which did not differ significantly from each other. The crowding threshold did not differ significantly among children, (9.9, 9.7, and 7.8 times stroke width for 5-, 8-, and 11-year-olds, respectively) but decreased significantly to 3.5 times the threshold stroke width in adults. Thus, single letter acuity is mature by age 8 but even 11-year-olds need more space between adjacent contours than do adults to avoid the deleterious effects of crowding. According to current theories (Levi, 2007; Motter, 2002; Pelli et al., 2007), crowding occurs when features of stimuli are inappropriately combined. Therefore, the stronger influence of crowding on younger children might be caused by immaturities in the brain areas where early visual inputs are combined, such as V4.
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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 | 0.002 | 0.001 |
| 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) | 0.002 | 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".