PREDICTING THE PARTURITION DATE IN YORKISHIRE TERRIER AND GOLDEN RETRIEVER BITCHES USING ULTRASONOGRAPHIC FETOMETRY
Bibliographic record
Abstract
The aim of this study was to evaluate the suitability of the ultrasonographic fetometry involving inner chorionic cavity diameter (ICC) and biparietal diameter (BP) measurements for predicting the parturition date in two dog breeds: the Yorkshire Terrier and Golden Retriever. Additionally, the authors studied whether developing specific mathematical formulas for predicting parturition dates in the breeds was justified. In the group of Yorkshire Terrier bitches, 12 ICC measurements and 14 BP measurements were taken. In the Golden Retrievers the ICC was measured 8 times and BP – 10 times. The obtained values were substituted into Luvoni–Grioni formulas, taking into account the body mass before pregnancy. Due to the lack of earlier studies on dogs with a body mass over 25 kg, the parturition date for the Golden Retrievers was calculated using formulas for medium–sized dogs (body mass 10–25 kg). In the case of the Yorkshire Terriers, formulas for dogs smaller than 10 kg were used. The method proved to be highly useful in predicting the accuracy of the parturition date in both breeds. Prediction accuracy in the Golden Retrievers reached 80% to 100%, depending on the type of measurement used, and precision levels. In the Yorkshire Terriers, the accuracy reached 57%–93%. Comparing the effectiveness of the parturition date prediction in the two breeds, no statistically significant differences were found. Regression lines based on the authors’ own fetometric measurements were highly convergent with the lines defined by the Luvoni–Grioni formulas. The only statistically significant difference was found in BP measurements in the Golden Retrievers; this suggests that the commonly used Luvoni–Grioni formula should be modified when applied to large dog breeds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".