Interobserver agreement on visual field progression in glaucoma: a comparison of methods
Bibliographic record
Abstract
AIM: To examine the level of agreement between clinicians in assessing progressive deterioration in visual field series using two different methods of analysis. METHODS: Each visual field series satisfied the following criteria: more than 19 reliable fields, patient age over 40 years, macular threshold at least 30 dB. The first three fields in each series were excluded to minimise learning effects: the following 16 were studied. Five expert clinicians assessed the progression status of each series using both standard Humphrey printouts and pointwise linear regression (PROGRESSOR). The level of agreement between the clinicians was evaluated using a weighted kappa statistic. RESULTS: A total of 432 tests comprising 27 visual field series of 16 tests each were assessed by the clinicians. The level of agreement on progression status between the clinicians was always higher when they used PROGRESSOR (median kappa = 0.59) than when they used Humphrey printouts (median kappa = 0.32). This was statistically significant (p = 0.006, Wilcoxon matched pairs signed rank sum test). CONCLUSIONS: Agreement between expert clinicians about visual field progression status is poor when standard Humphrey printouts are used, even when the field series studied are long and consist solely of reliable fields. Under these ideal conditions, clinicians agree more closely about patients' visual field progression status when using PROGRESSOR than when inspecting series of Humphrey printouts.
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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 | 0.082 | 0.174 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".