A comparison of white-to-white measurements obtained by Anterion AS-OCT versus three optical devices in refractive surgery candidates
Bibliographic record
Abstract
Background and ObjectivesTo assess the agreement between Anterion AS-OCT and three optical devices in measuring the white-to-white (WTW) diameter in candidates for refractive surgery.MethodsIn this cross-sectional prospective study, 129 right eyes of 129 normal individuals underwent consecutive scans with the Anterion, the Pentacam AXL, the IOLMaster 700, and the Orbscan IIz. Mean difference (MD), 95% limits of agreement (LoA), and concordance correlation coefficient (CCC) were calculated to assess agreement and interchangeability.ResultsThe mean age of participants was 30.4 ± 5.9 (range: 21-47) years. The mean WTW distance measured by the different instruments was as follows: 12.00 ± 0.42 mm (range, 10.57 to 13.05) using the Anterion, 11.87 ± 0.34 (11.10 to 12.80) using the Pentacam, 12.12 ± 0.44 (11.00 to 13.30) using the IOLMaster, and 11.73 ± 0.37 (11.00 to 13.10) using the Orbscan. The MD and 95% LoA for Anterion vs. Pentacam, IOLMaster, or Orbscan were [0.11; -0.31 to 0.54 mm], [-0.13; -0.93 to 0.66], and [0.25; -0.28 to 0.78], respectively. The corresponding CCCs were 0.803, 0.514, and 0.631.ConclusionsThis study found weak agreement between Anterion and Pentacam AXL, IOLMaster 700, and Orbscan IIz devices regarding WTW distance measurements in refractive surgery candidates. Therefore, it is not recommended to use Anterion's WTW measurements interchangeably with the other three devices, particularly for phakic intraocular lens sizing.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".