Localising rectus muscle insertions using high frequency wide-field ultrasound biomicroscopy
Bibliographic record
Abstract
AIM: The ultrasound biomicroscope (UBM) can accurately locate an extraocular muscle (EOM) insertion. The authors compared the accuracy of the Sonomed UBM (SUBM), a new 'wide-field ultrasound biomicroscope', with the older model Humphrey UBM (HUBM) in localising EOM insertions and compared their ranges of detection of muscle insertions. METHODS: Prospective, double-masked, observational study of 27 patients undergoing primary (n=40 muscles) or repeat (n=10 muscles) horizontal or vertical rectus muscle surgery. EOM insertional distances were measured with SUBM, and then intraoperatively with callipers. A Bland-Altman analysis and intraclass correlation coefficient were used to compare the SUBM and surgical data. RESULTS: For all muscles, the differences between SUBM and surgery measurements were less than 1.0 mm. The mean of the SUBM insertion distances was 6.67 mm (SD 1.65 mm) versus 6.7 mm (SD 1.6 mm) at surgery. The intraclass correlation coefficient showed 'excellent' correlation between the two sets of data and was higher than that reported with HUBM. The image quality with the SUBM was superior to the HUBM, and its range of field was much larger (14×18 mm vs 5×6 mm). CONCLUSION: The SUBM with its smaller, more manoeuvrable probe handpiece and a wider scanning field was more accurate in detecting muscle insertions compared with HUBM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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 teacher head, 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".