What Is Your Diagnosis?
Bibliographic record
Abstract
An 11-year-old spayed female Weimaraner was referred to the University of Tennessee College of Veterinary Medicine for evaluation of lethargy, decreased appetite, vomiting, weight loss, and melena of 3 months' duration.On physical examination, a mass was palpated in the middle portion of the abdomen.A CBC revealed severe microcytic hypochromic regenerative anemia (Hct, 14.7% [reference range, 41% to 60%]; mean corpuscular volume, 56.2 fL [reference range, 62 to 74 fL]; and reticulocyte count, 545 X 10 3 reticulocytes/µL [reference range, 12.5 X 10 3 reticulocytes/µL to 93 X 10 3 reticulocytes/µL]) and leukocytosis (WBC count, 32.9 X 10 3 WBCs/µL [reference range, 5.1 X 10 3 WBCs/ µL to 14 X 10 3 WBCs/µL]; neutrophil count, 29.9 X 10 3 neutrophils/µL [reference range, 2.65 X 10 3 neutrophils/µL to 9.8 X 10 3 neutrophils/µL]).Clinically relevant findings on serum biochemical analysis included hypoproteinemia (5.3 g/dL; reference range, 5.6 to 7.6 g/dL), hypoalbuminemia (2.0 g/dL; reference range, 3.1 to 4.2 g/dL), hypokalemia (2.9 mEq/L; reference range, 3.6 to 5.1 mEq/L), and hypocalcemia (9.6 mg/dL; reference range, 9.9 to 11.5 mg/dL).Abdominal radiographs were obtained (Figure 1).Determine whether additional imaging studies are required, or make your diagnosis from Figure 1-then turn the page
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.007 |
| 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".