Sonographic characteristics of presumptively normal main axillary and superficial cervical lymph nodes in dogs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the B-mode and Doppler ultrasonographic appearance of presumptively normal main axillary and large superficial cervical lymph nodes (MALNs and SCLNs, respectively) in adult dogs. ANIMALS: 51 healthy adult dogs (data from 1 dog were not analyzed). PROCEDURES: For each dog, weight, distance from the cranial aspect of the first sternebra to the caudal aspect of the left ischiatic tuberosity, and thoracic height and width at the level of the xiphoid process were recorded. Via B-mode and Doppler ultrasonography, echogenic characteristics, size in relation to body size and weight, and vascular supply of the MALNs and the SCLNs were evaluated (1 SCLN in 1 dog was not ultrasonographically visible). RESULTS: Most MALNs were clearly margined, solitary, and ovoid; echopatterns were homogenous or cortical and hypo- to isoechoic, compared with surrounding soft tissues. Size measurements of MALNs correlated with dogs' body length, thoracic width and height, and body weight. Most SCLNs were clearly margined, fusiform, and hypoechoic (compared with surrounding soft tissues) with a cortical or homogenous echopattern. Size measurements of SCLNs correlated with dogs' body length, thoracic width and height, and body weight. In 50 of the 100 MALNs, an intranodal vascular supply was detected; in contrast, an intranodal vascular supply in SCLNs was detected infrequently. CONCLUSIONS AND CLINICAL RELEVANCE: Results indicated that, in dogs, anatomically separate lymph nodes have different echogenic and vascular characteristics; body size (skeletal length, height, and width), along with body weight, were correlated with sizes of presumptively normal MALNs and SCLNs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".