Two-point Dixon and six-point Dixon magnetic resonance techniques in the detection, quantification and grading of hepatic steatosis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Hepatic steatosis is a very common problem worldwide. AIM: To assess the performance of two- and six-point Dixon magnetic resonance (MR) techniques in the detection, quantification and grading of hepatic steatosis. METHODS: A single-center retrospective study was performed in 62 patients with suspected parenchymal liver disease. MR sequences included two-point Dixon, six-point Dixon, MR spectroscopy (MRS) and MR elastography. Fat fraction (FF) estimates on the Dixon techniques were compared to the MRS-proton density FF (PDFF). Statistical tests used included Pearson's correlation and receiver operating characteristic. RESULTS: < 0.01). CONCLUSION: Dixon techniques performed satisfactorily for the evaluation of hepatic steatosis but with exceptions.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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 it