Inflammatory bowel disease characterized by multisystemic eosinophilic epitheliotropic disease (MEED) in a horse in Saskatchewan, Canada.
Bibliographic record
Abstract
A 3-year-old Quarter Horse gelding was evaluated for chronic weight loss, diarrhea, and pruritus. Physical examination revealed several ulcerative lesions on the skin and mucosal membranes. Diagnostic imaging findings were consistent with enteritis, typhlitis, and colitis. Multisystemic eosinophilic epitheliotropic disease (MEED) was diagnosed upon necropsy. This disease may be considered a form of equine inflammatory bowel disease complex which can be challenging to diagnose, requiring histological assessment, and in some cases, the use of immunohistochemical markers. Key clinical message: Multisystemic eosinophilic epitheliotropic disease is challenging to diagnose but should be considered in horses with chronic weight loss that fail to respond to conventional treatment for concurrent diarrhea and skin lesions.
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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) | 0.001 | 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 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".