Indications for Orbital Imaging by the Oculoplastic Surgeon
Bibliographic record
Abstract
OBJECTIVE: To determine the indications for ordering orbital imaging and the indications for ordering CT versus MRI by oculoplastic surgeons and to assess the correlation between surgeon's clinical indications for imaging and the radiologist's diagnosis. DESIGN: Retrospective review of imaging requisitions and radiology reports. PARTICIPANTS: Patients of 4 oculoplastic surgeons who required CT or MRI scans. METHODS: Imaging requisitions and radiology reports of patients from 4 oculoplastic surgeons were reviewed to determine the indication for ordering a CT or MRI scan between March 2006 and March 2009. The indications were then compared with the radiologist's diagnosis. RESULTS: A total of 735 patients were included: 449 (61.1%) female and 286 (38.9%) male, with an average age of 50.1 years and an age range of 7 months to 93 years. Of these patients, a total of 632 CT and 223 MRI scans were ordered, 135 of which were follow-up scans. CONCLUSIONS: The most common indication for CT scan was thyroid disease, followed by orbital tumors and then inflammatory disease, while the most common indication for MRI scan was orbital tumors, followed by inflammatory disease and then thyroid disease. CT scans were more commonly ordered than MRI, largely for trauma and to rule out orbital foreign body.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".