Ovary: MRI characterisation and O-RADS MRI
Bibliographic record
Abstract
Ultrasound has a high specificity for the diagnosis of a benign lesion in cases of classic appearing simple cyst, hemorrhagic cyst, endometrioma and dermoid. However, ultrasound can sometimes be limited for definitive characterisation and risk stratification of other types of lesions, including those with echogenic content that may appear solid, with or without blood flow. Frequently, MRI can be used to further characterise these types of lesions, due to its ability to distinguish solid tissue from non-tissue solid components such as fat, blood, or debris. Incorporating the MR imaging into the evaluation of adnexal lesions can improve diagnostic certainty and guide clinical management potentially avoiding inappropriate surgery for benign lesions and expediting appropriate treatment for malignant lesions, particularly in the females with sonographically indeterminate adnexal lesions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".