Estimation of sexual dimorphism in a population of dogs of the Romanian Mioritic Shepherd Dog breed
Bibliographic record
Abstract
Romanian Mioritic Shepherd Dog, was selected from a natural population breed of Romanian Carpathian Mountains. The aim of this study was to analyze the existence and size of sexual dimorphism in a population of 26 males and 23 females of the Mioritic Shepherd Dog breed, for 6 body measurements: ear length, ear width, distance between the ears, distance between the eyes, length hair at withers and metacarpal perimeter. Following the study on the significance of statistical differences between body measurements recorded in 26 males and 23 females, it was concluded that sexual dimorphism is not evident in the population of the Romanian Mioritic Shepherd Dog studied in this paper, except the distance between the ears character. Among the other characters, the differences between the individuals of the two sexes are insignificant (p>0.05). We recommend to the dog breeders to take into account the genetic improvement programs, and also the results presented in this paper.
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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".