Development of New Phenotyping Strategies to Allow for Real-time Belly Primal Selection in Canadian Breeding Hogs
Bibliographic record
Abstract
This thesis investigated the use of real-time ultrasound for prediction of belly traits in Canadian breeding hogs. Bellies from 17 pigs had the first sixteen 1” strips removed and analysed for fat and muscle distributions. Locations with strong correlations to the rest of the belly that were suitable for live ultrasound scans were identified as between the 3rd and 4th last ribs halfway down the side of the pig and 2-3” below the first location. 323 purebred Duroc and Pietrain gilts were live-scanned using the aforementioned locations for depths of subcutaneous fat, cutaneous trunci (CT), and belly cut. Multiple regressions adjusted for Weight and Date to predict carcass measures from ultrasound measures produced R2 of 0.34, 0.23, and 0.38, for Fat, CT, and Cut, respectively. Heritability estimates from univariate models of belly traits were 0.42, 0.16, 0.27, 0.20, 0.21, and 0.16 for BF, Cut, Sfat1, Scut1, Sfat2, and Scut2, respectively.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".