Multi-modality imaging review of congenital abnormalities of kidney and upper urinary tract
Bibliographic record
Abstract
Congenital abnormalities of the kidney and urinary tract (CAKUT) include a wide range of abnormalities ranging from asymptomatic ectopic kidneys to life threatening renal agenesis (bilateral). Many of them are detected in the antenatal or immediate postnatal with a significant proportion identified in the adult population with varying degree of severity. CAKUT can be classified on embryological basis in to abnormalities in the renal parenchymal development, aberrant embryonic migration and abnormalities of the collecting system. Renal parenchymal abnormalities include multi cystic dysplastic kidneys, renal hypoplasia, number (agenesis or supernumerary), shape and cystic renal diseases. Aberrant embryonic migration encompasses abnormal location and fusion anomalies. Collecting system abnormalities include duplex kidneys and Pelvi ureteric junction obstruction. Ultrasonography (US) is typically the first imaging performed as it is easily available, non-invasive and radiation free used both antenatally and postnatally. Computed tomography (CT) and magnetic resonance imaging (MRI) are useful to confirm the ultrasound detected abnormality, detection of complex malformations, demonstration of collecting system and vascular anatomy and more importantly for early detection of complications like renal calculi, infection and malignancies. As CAKUT are one of the leading causes of end stage renal disease, it is important for the radiologists to be familiar with the varying imaging appearances of CAKUT on US, CT and MRI, thereby helping in prompt diagnosis and optimal management.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".