B-Mode and doppler sonography of the mammary glands in dairy goats for mastitis diagnosis
Bibliographic record
Abstract
Contents This study aimed to evaluate the sonographic characteristics of the udder and teats and to determine the Doppler indexes of mammary artery in healthy and undergoing subclinical and clinical mastitis goats. Thirty animals among Saanen and Alpine Brown goats were arranged in three groups, healthy goats (HG), goats with subclinical mastitis (SMG) and goats with clinical mastitis (CMG). Using the B-mode, the sonographic characteristics (echotexture and echogenicity) and biometry (diameter and area of the udder cistern, diameter and area of the teat cistern and thickness of the teat wall) were evaluated. Using Doppler ultrasonography, the vascular indexes of the mammary artery were obtained. It was observed hyperechogenicity with solid component in the gland cistern when comparing animals with clinical mastitis and healthy mammary tissue. Regarding the echotexture of the breast tissue, there was heterogeneity in the mammary parenchyma on the three groups, for the milk, it was observed homogeneity for animals on HG and SMG and heterogeneity for animals on CMG. Grey-scale quantitative assessment revealed increase in echogenicity (mean value) for all the structures when comparing the three groups. Biometry did not reveal statistical difference between groups, for none of the evaluated structures. Doppler examination of the mammary artery showed the decrease of end diastolic velocity and raise of pulsatility index between groups. The association of B-mode and Doppler ultrasonography is useful for the evaluation of the udder of dairy goats with mastitis. It is a sensitive and specific method for the study of this disease. Doppler mode was unable to establish reliable criteria for diagnosis of subclinical mastitis. Moreover, the quantification of echogenicity is a useful technique for the evaluation of the milk in animals with mastitis; therefore, it is suggested that it can be used as complementary technique for the diagnosis of mastitis in goats.
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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 | 0.001 |
| 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".