ACR Appropriateness Criteria® Clinically Suspected Adnexal Mass
Bibliographic record
Abstract
Adnexal masses are a common problem clinically and imaging-wise, and transvaginal US (TVUS) is the first-line imaging modality for assessing them in the vast majority of patients. The findings of US, however, should be correlated with the history and laboratory tests, as well as any patient symptoms. Simple cysts are uniformly benign, and most warrant no further interrogation or treatment. Complex cysts carry more significant implications, and usually engender serial ultrasound(s), with a minority of cases warranting a pelvic MRI.Morphological analysis of adnexal masses with gray-scale US can help narrow the differential diagnosis. Spectral Doppler analysis has not proven useful in most well-performed studies. However, the use of color Doppler sonography adds significant contributions to differentiating between benign and malignant masses and is recommended in all cases of complex masses. Malignant masses generally demonstrate neovascularity, with abnormal branching vessel morphology. Optimal sonographic evaluation is achieved by using a combination of gray-scale morphologic assessment and color or power Doppler imaging to detect flow within any solid areas.The ACR Appropriateness Criteria® are evidence-based guidelines for specific clinical conditions that are reviewed every two years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".