Chronic, circumferential forelimb wound and lameness in a 4-year-old male castrated Labradoodle
Bibliographic record
Abstract
A 4-year-old 38.4-kg castrated male Labrador Retriever-Poodle cross was presented to Texas A&M University's Small Animal Emergency Service because of left thoracic limb lameness.The dog was initially presented to another emergency clinic 4 weeks prior due to licking at the left carpus and favoring the left forelimb.The left carpus was clipped, and a circumferential wound was identified and treated with hydrotherapy, bandage changes, cold laser therapy, and two 1-week courses of clindamycin over that month.The week prior to presentation at our hospital, the dog became non-weight-bearing on the limb.On initial examination at our referral hospital, the dog was bright and alert with vital signs within normal limits.There was a firm, painful swelling over the left distal antebrachium proximal to the carpal joint, and a circumferential dermal scar with a soft, fluid-filled area on the caudomedial aspect of the scar.There was no open draining tract.The dog was non-weight-bearing and knuckling on the left forelimb on gait examination.On neurologic examination, the dog had an absent withdrawal, marked muscle atrophy, and no appreciable deep pain distal to the carpus in the left thoracic limb.Baseline bloodwork showed a mild leukocytosis (WBC count, 17.5 X 10 3 WBCs/µL; reference range, 6 X 10 3 to 17 X 10 3 WBCs/µL), mature neutrophilia (14.35 X 10 3 neutrophils/µL; reference range, 0.3 X 10 3 to 11.5 X 10 3 neutrophils/µL), and mildly elevated globulins (4.1 g/dL; reference range, 1.7 to 3.8 g/dL).All other results were within reference ranges.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".