Phenotypic Characteristics Including In Vivo Cone Photoreceptor Mosaic in<i>KCNV2-</i>Related “Cone Dystrophy with Supernormal Rod Electroretinogram”
Bibliographic record
Abstract
PURPOSE: To report phenotypic characteristics including macular cone photoreceptor morphology in KCNV2-related "cone dystrophy with supernormal rod electroretinogram" (CDSR). METHODS: Seven patients, aged 9 to 18 years at last visit, with characteristic full-field electroretinographic (ERG) features of CDSR were screened for mutations in the KCNV2 gene. All patients underwent detailed ophthalmological evaluation, which included distance and color vision testing, contrast sensitivity measurement, fundus photography, fundus autofluorescence (FAF) imaging, and spectral domain-optical coherence tomography (SD-OCT). Follow-up visits were available in six cases. Rod photoreceptor function was assessed using a bright white flash ERG protocol (240 cd·s/m(2)). Macular cone photoreceptor morphology was assessed from 2° by 2° zonal images obtained using adaptive optics scanning laser ophthalmoscopy (AOSLO) in six cases. RESULTS: Pathogenic mutations in KCNV2 were identified in all seven cases. Best corrected vision was 20/125 or worse in all cases at the latest visit (20/125-20/400). Vision loss was progressive in two cases. Color vision and contrast sensitivity was abnormal in all cases. Retinal exam revealed minimal pigment epithelial changes at the fovea in four cases. A peri- or parafoveal ring of hyperfluorescence was the most common FAF abnormality noted (five cases). The SD-OCT showed outer retinal abnormalities in all cases. The rod photoreceptor maximal response was reduced but rod sensitivity was normal. AOSLO showed markedly reduced cone density in all six patients tested. CONCLUSIONS: Central vision parameters progressively worsen in CDSR. Structural retinal and lipofuscin accumulation abnormalities are commonly present. Macular cone photoreceptor mosaic is markedly disrupted early in the disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".