Faculty Opinions recommendation of Early visual-evoked potential acuity and future behavioral acuity in cortical visual impairment.
Bibliographic record
Abstract
Purpose-Cortical Visual Impairment (CVI) is bilateral visual impairment caused by damage to the posterior visual pathway.Both preferential looking (PL) and sweep visual evoked potential (VEP) can be used to measure visual acuity.The purpose of this study was to determine if an early VEP measure of acuity is related to a young patient's future behavioral acuity.Methods-The visual acuity of 33 patients with CVI was assessed using the sweep VEP and a behavioral measure on two occasions.The median age of the patients at the initial visit was 4.8 years (range: 1.3-19.2years), and they were followed for an average of 6.9 years (SD: 3.5 years).Results-The mean initial VEP acuity was 20/135 (0.735 logMAR), and the mean initial behavioral acuity was 20/475 (1.242 logMAR).The average difference between the two initial measures of acuity was 0.55 log unit, with the behavioral measure reporting a poorer visual acuity in all patients.However, the mean final behavioral acuity was 20/150 (0.741 logMAR), and the average difference between the initial VEP acuity and the final behavioral acuity was only 0.01 log unit.Therefore, the initial VEP measure was not statistically different from the final behavioral measure (t=0.11;df=32; p=0.45).Conclusions-Even though the initial VEP measure was much better than the initial behavioral measure, the initial VEP measure was similar to the behavioral visual acuity measured approximately 7 years later.Sweep VEP testing can be used as a predictive tool for at least the lower limit of future behavioral acuity in young patients with CVI.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.053 | 0.021 |
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".