LOSS OF UROCYSTOLITH ARCHITECTURAL CLARITY DURING IN VIVO RADIOGRAPHIC SIMULATION VERSUS IN VITRO VISUALIZATION
Bibliographic record
Abstract
Urocystoliths of 9 mineral types from 434 canine patients submitted to the University of Minnesota Urolith Bank were imaged in a urinary bladder phantom. Imaging techniques simulated were survey radiography and double contrast cystography. Morphologic characteristics visually observed in vitro or by interpretation of high-resolution specimen radiographs were compared to those seen using the simulated in vivo imaging techniques. Shape characteristics that were accurately detected > or = 25% of the time on simulated survey or double contrast radiography were faceted, irregular, jackstone, ovoid, and round. Surface characteristics that were accurately detected > or = 25% of the time on simulated survey or double contrast radiography were rough, smooth, and smooth with blunt tips. Internal architecture characteristics that were accurately detected > or = 25% of the time on simulated survey or double contrast radiography were lucent center, random-nonuniform, and uniform. Shapes such as bosselated, faceted-ovoid, and rosette; surfaces such as botryoidal, and knife-edged; and internal architecture characteristics such as dense center, dense shell, laminated, and fissures were of almost no value either due to poor detectability or poor accuracy of recognition. Based on optimized simulated survey and double contrast radiographic procedures, it appears that a number of shape, surface, and internal architecture characteristics may be of limited or no value in discriminating among urocystolith mineral types under clinical circumstances. Shapes and surfaces were more accurately characterized by the simulated double contrast technique, but for internal architecture, the simulated survey radiographic technique seemed slightly superior overall.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".