186 QUANTITATIVE ECHOGENICITY AND ECHOTEXTURE ANALYSIS OF THE ACCESSORY SEX GLANDS OF PUBERTAL AND MATURE DORPER RAMS
Bibliographic record
Abstract
This study aimed to analyse the ultrasonographic attributes of vesicular, prostate, and bulbourethral glands in pubertal and mature Dorper rams. Forty-five rams were used in the same day (pubertal: 8–11 months, n = 24; mature: =12 months, n = 21). The B-mode ultrasounds examinations were performed using MyLab 30Vet equipment (Esaote, Naples, Italy) connected to transrectal linear transducer (frequency of 7.5 MHz). The echogenicity [(mean numerical pixel values (NPV)] and pixel heterogeneity (standard deviation of NPV) of accessory sex glands parenchymas was determined by computerised image analysis using Image ProPlus® software (Media Cybernetics Inc., Rockville, MD, USA). For the pairs organs a mean for each parameter were calculated. Data were analysed by ANOVA with Tukey test (mean ± s.d.; P < 0.05), after the normality and homoscedasticity of residuals were checked with Shapiro-Wilk test and Levene test, respectively, when necessary log-transformation was applied. All statistical procedures was performed with R® software. The echogenicity of parenchymas were different (P < 0.05) between pubertal and mature rams for vesicular glands (181.51 ± 20.80 v. 164.83 ± 26.79) and bulbourethral glands (166.93 ± 16.93 v. 141.80 ± 29.15); however, there was no difference (P > 0.05) for prostate glands (99.39 ± 36.34 v. 87.47 ± 34.24). The pixel heterogeneity did not differ (P > 0.05) between pubertal and mature rams (29.06 ± 2.67 v. 28.09 ± 3.95, 32.14 ± 8.20 v. 30.28 ± 4.71, and 27.82 ± 4.53 v. 28.74 ± 4.29) for vesicular, prostate, and bulbourethral glands, respectively. In conclusion, the sexual maturity only influenced the echogenicity of vesicular and bulbourethral parenchymas of Dorper rams.
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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 | 0.000 |
| 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) | 0.002 | 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".