Deficient Motion-Defined and Texture-Defined Figure–Ground Segregation in Amblyopic Children
Bibliographic record
Abstract
PURPOSE Motion-defined form deficits in the fellow eye and the amblyopic eye of children with amblyopia implicate possible direction-selective motion processing or static figure–ground segregation deficits. Deficient motion-defined form perception in the fellow eye of amblyopic children may not be fully accounted for by a general motion processing deficit. This study investigates the contribution of figure–ground segregation deficits to the motion-defined form perception deficits in amblyopia. METHODS Performances of 6 amblyopic children (5 anisometropic, 1 anisostrabismic) and 32 control children with normal vision were assessed on motion-defined form, texture-defined form, and global motion tasks. RESULTS Performance on motion-defined and texture-defined form tasks was significantly worse in amblyopic children than in control children. Performance on global motion tasks was not significantly different between the 2 groups. CONCLUSION Faulty figure–ground segregation mechanisms are likely responsible for the observed motion-defined form perception deficits in amblyopia. J Pediatr Ophthalmol Strabismus 2007;44:363-371. AUTHORS Ms. Wang and Dr. Giaschi are from the Department of Ophthalmology and Visual Sciences, University of British Columbia, Children’s and Women’s Health Centre of British Columbia, Vancouver, British Columbia, Canada. Drs. Ho and Giaschi are from the Department of Psychology, University of British Columbia, Vancouver, British Columbia, Canada. Originally submitted May 31, 2005. Accepted for publication May 5, 2006. Address correspondence to Deborah E. Giaschi, PhD, Department of Ophthalmology, Room A146, BC’s Children’s Hospital, 4480 Oak Street, Vancouver, BC, V6H 3V4, Canada. Supported by NSERC grant 194526 (Dr. Giaschi), and by the British Columbia Research Institute in Children’s and Women’s Health and the Canadian Optometric Education Trust Fund (Dr. Ho). The authors thank Roy Cline, Christopher Lyons, and Megan Rees for providing clinical assessments.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".